System and method for capturing and generating panoramic three-dimensional images

Abstract

The invention discloses a system and a method for capturing and generating panoramic three-dimensional images. An apparatus includes a housing, a mount configured to be coupled to a motor to horizontally move the apparatus, a wide-angle lens coupled to the housing, the wide-angle lens positioned above the mount along an axis of rotation, an image capture device coupled to the wide-angle lens, and a LiDAR device coupled to the mount. The apparatus includes a housing having an axis of rotation, the axis of rotation being an axis along which the apparatus rotates, an image capture device within the housing, the image capture device configured to receive a two-dimensional image of an environment through the wide-angle lens, and a LiDAR device within the housing, the LiDAR device configured to generate depth data based on the environment.

Description

[0001] This application is a divisional application of Chinese patent application 202080084506.9 (PCT / US2020 / 067474) filed on December 30, 2020, entitled “System and method for capturing and generating panoramic three-dimensional images”. Technical Field

[0002] Embodiments of the present invention generally relate to capturing and stitching panoramic images of a scene in a physical environment. Background Art

[0003] The popularity of providing three-dimensional (3D) panoramic images of the physical world has given rise to many solutions that have the ability to capture multiple two-dimensional (2D) images and generate 3D images based on the captured 2D images. There are hardware solutions and software applications (or "apps") that can capture multiple 2D images and stitch them into a panoramic image.

[0004] Technologies exist for capturing and generating 3D data from buildings. However, existing technologies are often unable to capture and generate 3D renderings of areas in bright lighting. Sunlight shining through windows or areas of floor or wall in bright lighting often appear as holes in 3D renderings, which may require additional post-production work to fill. This increases the turnaround time and realism of 3D renderings. Furthermore, outdoor environments present challenges for many existing 3D capture devices, as structured light may not be designed to capture 3D images.

[0005] Other limitations of existing techniques for capturing and generating 3D data include the amount of time required to capture and process the digital images needed to produce a 3D panoramic image. Summary of the Invention

[0006] An example device includes a housing, a mount configured to be coupled to a motor to move the device horizontally, a wide-angle lens coupled to the housing, the wide-angle lens positioned above the mount so as to be along a rotational axis, the rotational axis being the axis along which the device rotates when coupled to the motor, an image capture device within the housing, the image capture device configured to receive a two-dimensional image of an environment through the wide-angle lens, and a LiDAR device within the housing, the LiDAR device configured to generate depth data based on the environment.

[0007] An image capture device may include a housing, a first motor, a wide-angle lens, an image sensor, a mount, a LiDAR (Light Detection and Ranging) sensor, a second motor, and a reflector. The housing may have a front side and a rear side. The first motor may be coupled to the housing at a first position between the front side and the rear side of the housing, the first motor being configured to rotate the image capture device horizontally substantially 270 degrees about a vertical axis. The wide-angle lens may be coupled to the housing at a second position between the front side and the rear side of the housing along the vertical axis, the second position being a point of no parallax, the wide-angle lens having a field of view away from the front side of the housing. The image sensor may be coupled to the housing and configured to generate an image signal from light received by the wide-angle lens. The mount may be coupled to the first motor. The LiDAR may be coupled to the housing at a third position, the LiDAR being configured to generate laser pulses and generate a depth signal. The second motor may be coupled to the housing. The mirror may be coupled to a second motor that may be configured to rotate the mirror about a horizontal axis, the mirror comprising an angled surface configured to receive the laser pulses from the LiDAR and direct the laser pulses about the horizontal axis.

[0008] In some embodiments, the image sensor is configured to generate a first plurality of images at different exposures when the image capture device is stationary and pointing in a first direction. The first motor can be configured to rotate the image capture device about the vertical axis after generating the first plurality of images. In various embodiments, the image sensor does not generate an image when the first motor rotates the image capture device, and wherein the LiDAR generates a depth signal based on the laser pulses when the first motor rotates the image capture device. The image sensor can be configured to generate a second plurality of images at the different exposures when the image capture device is stationary and pointing in a second direction, and the first motor is configured to rotate the image capture device 90 degrees about the vertical axis after generating the second plurality of images. The image sensor can be configured to generate a third plurality of images at the different exposures when the image capture device is stationary and pointing in a third direction, and the first motor is configured to rotate the image capture device 90 degrees about the vertical axis after generating the third plurality of images. The image sensor may be configured to generate a fourth plurality of images at the different exposures when the image capture device is stationary and pointed in a fourth direction, and the first motor may be configured to rotate the image capture device 90 degrees about the vertical axis after generating the fourth plurality of images.

[0009] In some embodiments, the system may further include a processor configured to blend frames of the first plurality of images before the image sensor generates the second plurality of images. A remote digital device may be in communication with the image capture device and configured to generate a 3D visualization based on the first, second, third, and fourth plurality of images and the depth signal, the remote digital device being configured to use no more than the first, second, third, and fourth plurality of images to generate the 3D visualization. In some embodiments, the first, second, third, and fourth plurality of images are generated between rotations that combine to rotate the image capture device 270 degrees about the vertical axis. The speed or rotation of the reflector about the horizontal axis increases as the first motor rotates the image capture device. The angled surface of the reflector may be 90 degrees. In some embodiments, the LiDAR emits the laser pulses in a direction opposite to the front side of the housing.

[0010] An example method includes receiving light from a wide angle lens of an image capture device, the wide angle lens coupled to a housing of the image capture device, the light being received at a field of view of the wide angle lens, the field of view extending away from a front side of the housing, generating a first plurality of images by an image sensor of the image capture device using the light from the wide angle lens, the image sensor coupled to the housing, the first plurality of images being at different exposures, rotating the image capture device horizontally substantially 270 degrees about a vertical axis by a first motor, the first motor coupled to the housing in a first position between the front and rear sides of the housing, the wide angle lens being at a second position along the vertical axis, the second position being a zero-parallax point, rotating a mirror having an angled surface about a horizontal axis by a second motor, the second motor coupled to the housing, generating laser pulses by a LiDAR, the LiDAR coupled to the housing at a third position, the laser pulses being directed to the rotating mirror as the image capture device is rotated horizontally, and generating a depth signal by the LiDAR based on the laser pulses.

[0011] Generating the first plurality of images by the image sensor may occur before the image capture device is rotated horizontally. In some embodiments, the image sensor does not generate images when the first motor rotates the image capture device, and wherein the LiDAR generates the depth signal based on the laser pulses when the first motor rotates the image capture device.

[0012] The method may further include generating, by the image sensor, a second plurality of images with the different exposures while the image capture device is stationary and pointing in a second direction, and rotating the image capture device 90 degrees about the vertical axis by the first motor after generating the second plurality of images.

[0013] In some embodiments, the method may further include generating, by the image sensor, a third plurality of images at the different exposures while the image capture device is stationary and pointing in a third direction, and rotating the image capture device 90 degrees about the vertical axis via the first motor after generating the third plurality of images. The method may further include generating, by the image sensor, a fourth plurality of images at the different exposures while the image capture device is stationary and pointing in a fourth direction. The method may include generating a 3D visualization based on the depth signal using the first, second, third, and fourth plurality of images, without using any other images.

[0014] In some embodiments, the method may further include blending frames of the first plurality of images before the image sensor generates the second plurality of images. The first, second, third, and fourth pluralities of images may be generated between rotations that combine to rotate the image capture device 270 degrees about the vertical axis. In some embodiments, the speed or rotation of the mirror about the horizontal axis increases as the first motor rotates the image capture device. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIG. 1 a depicts a dollhouse view of an example environment, such as a house, in accordance with some embodiments.

[0016] FIG. 1 b depicts a plan view of a first floor of a house, according to some embodiments.

[0017] Figure 2 Depicted is an example eye-level view of a living room, which may be part of a virtual tour.

[0018] Figure 3 An example of an environment capture system in accordance with some embodiments is depicted.

[0019] Figure 4 Depicted is a perspective view of an environment capture system in some embodiments.

[0020] Figure 5 is a depiction of laser pulses from a LiDAR surrounding an environment capture system in some embodiments.

[0021] Figure 6A A side view of the environmental capture system is depicted.

[0022] Figure 6B Depicted is a view of capturing a system from above from the environment in some embodiments.

[0023] Figure 7 Depicted is a perspective view of components of one example of an environment capture system in accordance with some embodiments.

[0024] Figure 8A Example lens sizes are depicted in some embodiments.

[0025] Figure 8B Depicted are example lens design specifications for some embodiments.

[0026] 9A depicts a block diagram of an example of an environment capture system in accordance with some embodiments.

[0027] 9B depicts a block diagram of an example SOM PCBA of an environment capture system, according to some embodiments.

[0028] Figures 10a-10c Described is a process for an environment capture system in some embodiments for capturing images.

[0029] Figure 11 Depicted is a block diagram of an example environment capable of capturing and stitching images to form a 3D visualization, in accordance with some embodiments.

[0030] Figure 12 is a block diagram of an example of an alignment and stitching system according to some embodiments.

[0031] Figure 13 Depicted is a flow diagram of a 3D panoramic image capture and generation process in accordance with some embodiments.

[0032] Figure 14 Depicted is a flow diagram of a 3D and panoramic capture and stitching process in accordance with some embodiments.

[0033] Figure 15 Depicted showing Figure 14 A flow chart with further details of one step of the 3D and panoramic capture and stitching process.

[0034] Figure 16 Depicted is a block diagram of an example digital device in accordance with some embodiments. DETAILED DESCRIPTION

[0035] Many of the innovations described herein are presented with reference to the accompanying drawings. Like reference numerals are used to refer to like elements. In the following description, for purposes of explanation, numerous specific details are set forth to provide a thorough understanding. However, it will be apparent that various innovations can be practiced without these specific details. In other instances, well-known structures and components are shown in block diagram form to facilitate description of the innovations.

[0036] Various embodiments of the device provide users with 3D panoramic images of indoor and outdoor environments. In some embodiments, the device can effectively and quickly provide users with 3D panoramic images of indoor and outdoor environments using a single wide field of view (FOV) lens and a single light detection and ranging sensor (LiDAR sensor).

[0037] The following is an example use case for the example device described herein. The following use case is one of the embodiments. Different embodiments of the device as discussed herein may include one or more features and capabilities similar to those in this use case.

[0038] Figure 1a depicts a dollhouse view 100 of an example environment (e.g., a house) according to some embodiments. The dollhouse view 100 provides an overall view of the example environment captured by the environment capture system (discussed herein). A user can interact with the dollhouse view 100 on the user system by switching between different views of the example environment. For example, a user can interact with area 110 to trigger a floor plan view of the first floor of the house, as shown in Figure 1b. In some embodiments, a user can interact with icons (such as icons 120, 130, and 140) in the dollhouse view 100 to provide a walkthrough view (e.g., for 3D walkthrough), a floor plan view, or a measurement view, respectively.

[0039] Figure 1b depicts a floor plan view of the first floor of a house according to some embodiments. The floor plan view is a top-down view of the first floor of the house. A user can interact with an area of ​​the floor plan view, such as area 150, to trigger an eye-level view of a particular portion of the floor plan, such as a living room. An example of an eye-level view of the living room can be found in Figure 2 , which can be part of a virtual tour.

[0040] The user can interact with a portion of floor plan 200 corresponding to area 150 of Figure 1b. The user can move the view around the room as if the user were actually in the living room. In addition to the horizontal 360° view of the living room, the user can also view or navigate the floor or ceiling of the living room. In addition, the user can move through the living room to other parts of the house by interacting with specific areas of that portion of floor plan 200, such as areas 210 and 220. When the user interacts with area 220, the environment capture system can provide a walkable transition between an area of ​​the house that substantially corresponds to the block of the house depicted by area 150 to an area of ​​the house that substantially corresponds to the block of the house depicted by area 220.

[0041] Figure 3 One example of an environment capture system 300 is depicted in accordance with some embodiments. The environment capture system 300 includes a lens 310, a housing 320, a mounting attachment 330, and a removable cover 340.

[0042] When in use, the environment capture system 300 can be positioned in an environment such as a room. The environment capture system 300 can be positioned on a support (e.g., a tripod). The removable cover 340 can be moved to reveal the LiDAR and the rotatable reflector. Once activated, the environment capture system 300 can take a burst of images and then rotate using a motor. The environment capture system 300 can open the mounting attachment 330. While rotating, the LiDAR can take measurements (the environment capture system may not take images while rotating). Once pointed in a new direction, the environment capture system can take another burst of images before rotating to the next direction.

[0043] For example, once located, the user can command the environment capture system 300 to begin a sweep. The sweep can be as follows:

[0044] (1) Exposure estimation, and then capturing HDR RGB images

[0045] Rotate 90 degrees to capture depth data

[0046] (2) Exposure estimation, and then capturing HDR RGB images

[0047] Rotate 90 degrees to capture depth data

[0048] (3) Exposure estimation, and then capturing HDR RGB images

[0049] Rotate 90 degrees to capture depth data

[0050] (4) Exposure estimation, and then capturing HDR RGB images

[0051] Capture depth data by rotating 90 degrees (360 degrees total)

[0052] For each burst, there can be any number of images at different exposures. The environment capture system can blend any number of images from a burst together while waiting for another frame and / or waiting for the next burst.

[0053] The housing 320 can protect the electronic components of the environment capture system 300 and can provide an interface for user interaction with a power button, a scan button, etc. For example, the housing 320 can include a removable cover 340 that can be removable to expose the LiDAR. In addition, the housing 320 can include electronic interfaces such as a power adapter and indicator lights. In some embodiments, the housing 320 is a molded plastic housing. In various embodiments, the housing 320 is a combination of one or more of plastic, metal, and polymer.

[0054] Lens 310 may be part of a lens assembly. Further details of the lens assembly may be found in Figure 7 305. Lens 310 is strategically placed at the center of the rotation axis 305 of the environment capture system 300. In this example, the rotation axis 305 is in the xy plane. By placing lens 310 at the center of the rotation axis 305, parallax effects can be eliminated or reduced. Parallax is an error caused by the rotation of the image capture device around a point that is not a non-parallax point (NPP). In this example, the NPP can be found at the center of the lens' entrance pupil.

[0055] For example, assume a panoramic image of a physical environment is generated based on four images captured by environment capture system 300, where the images in the panoramic image have a 25% overlap. If parallax were not present, 25% of one image could completely overlap with another image of the same area of ​​the physical environment. Eliminating or reducing the parallax effect of the multiple images captured by the image sensor through lens 310 can facilitate stitching the multiple images into a 2D panoramic image.

[0056] Lens 310 may include a large field of view (eg, lens 310 may be a fisheye lens). In some embodiments, the lens may have a horizontal FOV (HFOV) of at least 148 degrees and a vertical FOV (VFOV) of at least 94 degrees.

[0057] Mounting attachment 330 may allow environment capture system 300 to be attached to a mount. The mount may allow environment capture system 300 to be coupled to a tripod, a flat surface, or a motorized mount (e.g., to move environment capture system 300). In some embodiments, the mount may allow environment capture system 300 to rotate along a horizontal axis.

[0058] In some embodiments, the environment capture system 300 may include a motor for horizontally rotating the environment capture system 300 about the mounting attachment 330 .

[0059] In some embodiments, the motorized mount can move the environment capture system 300 along a horizontal axis, a vertical axis, or both. In some embodiments, the motorized mount can rotate or move in the xy plane. The use of the mounting attachment 330 can allow the environment capture system 300 to be coupled to a motorized mount, a tripod, or the like to stabilize the environment capture system 300 to reduce or minimize shaking. In another example, the mounting attachment 330 can be coupled to a motorized mount that allows the 3D and environment capture system 300 to rotate at a stable, known speed, which helps the LiDAR determine the (x, y, z) coordinates of each laser pulse of the LiDAR.

[0060] Figure 4 A rendering of an environment capture system 400 in some embodiments is depicted. The rendering shows the environment capture system 400 (which may be a front view 410, a top view 420, a side view 430, and a rear view 440) from various views. Figure 3 ). In these renderings, environment capture system 400 may include an optional hollow portion depicted in side view 430.

[0061] In some embodiments, the environment capture system 400 has a width of 75 mm, a height of 180 mm, and a depth of 189 mm. It should be understood that the environment capture system 400 can have any width, height, or depth. In various embodiments, regardless of the specific measurements, the ratio of width to height to depth in the first example is maintained.

[0062] The housing of the 3D and environmental capture system 400 can protect the electronic components of the environmental capture system 400 and can provide an interface / interface for user interaction (e.g., the screen on the rear view 440). In addition, the housing can include electronic interfaces such as a power adapter and indicator lights. In some embodiments, the housing is a molded plastic housing. In various embodiments, the housing is a combination of one or more of plastic, metal, and polymer. The environmental capture system 400 can include a removable cover that can be removable to expose the LiDAR and protect the LiDAR from the elements when not in use.

[0063] The lens depicted on the front view 410 can be part of a lens assembly. Similar to the environmental capture system 300, the lens of the environmental capture system 400 is strategically placed at the center of the axis of rotation. The lens can include a large field of view. In various embodiments, the lens depicted on the front view 410 is concave and the housing is flared so that the wide angle lens is directly at the zero parallax point (e.g., directly above the midpoint of the mount and / or motor), but can still capture images without interference from the housing.

[0064] A mounting attachment at the base of the environment capture system 400 can allow the environment capture system to be attached to the mount. The mount can allow the environment capture system 400 to be coupled to a tripod, a flat surface, or a motorized mount (e.g., to move the environment capture system 400). In some embodiments, the mount can be coupled to an internal motor for rotating the environment capture system 400 about the mount.

[0065] In some embodiments, the mount can allow the environment capture system 400 to rotate along a horizontal axis. In various embodiments, the motorized mount can move the environment capture system 400 along a horizontal axis, a vertical axis, or both. The use of a mounting attachment can allow the environment capture system 400 to be coupled to a motorized mount, a tripod, or the like to stabilize the environment capture system 400 to reduce or minimize shaking. In another example, the mounting attachment can be coupled to a motorized mount that allows the environment capture system 400 to rotate at a stable, known speed, which helps the LiDAR determine the (x, y, z) coordinates of each laser pulse of the LiDAR.

[0066] In view 430, a reflector 450 is revealed. The LiDAR can transmit laser pulses to the reflector (in the opposite direction of the lens view). The laser pulses can hit the reflector 450, which can be angled (e.g., at a 90-degree angle). The reflector 450 can be coupled to an internal motor that rotates the reflector so that the LiDAR laser pulses can be transmitted and / or received at many different angles around the environment capture system 400.

[0067] Figure 5 is a depiction of laser pulses from a LiDAR around the environment capture system 400 in some embodiments. In this example, the laser pulses are emitted at a rotating mirror 450. The laser pulses can be emitted and received perpendicular to the horizontal axis 602 (see FIG6 ) of the environment capture system 400. The mirror 450 can be angled so that the laser pulses from the LiDAR are directed away from the environment capture system 400. In some examples, the angle of the angled surface of the mirror can be 90 degrees, or at or between 60 and 120 degrees.

[0068] In some embodiments, when the environment capture system 400 is stationary and in operation, the environment capture system 400 can capture a burst of images through the lens. The environment capture system 400 can activate the pan motor between bursts of images. When rotating along the mount, the LiDAR of the environment capture system 400 can emit and / or receive laser pulses that strike the rotating mirror 450. The LiDAR can generate a depth signal and / or generate depth data from the reflections of the received laser pulses.

[0069] In some embodiments, the depth data can be associated with coordinates with respect to the environment capture system 400. Similarly, pixels or portions of an image can be associated with coordinates with respect to the environment capture system 400 to enable the generation of 3D visualizations (e.g., images from different directions, 3D walkthroughs, etc.) to be generated using the image and depth data.

[0070] like Figure 5 As shown, the LiDAR pulses may be blocked by the bottom of the environment capture system 400. It will be appreciated that the mirror 450 may rotate in unison while the environment capture system 400 moves about the mount, or the mirror 450 may rotate more slowly when the environment capture system 400 begins to move and further when the environment capture system 400 slows to a stop (e.g., maintaining a constant speed between starting and stopping of the mount motor).

[0071] The LiDAR can receive depth data from the pulses. Due to the movement of the environment capture system 400 and / or the increase or decrease in the speed of the mirror 450, the density of the depth data about the environment capture system 400 may be inconsistent (e.g., denser in some areas and less dense in other areas).

[0072] FIG6 a depicts a side view of the environment capture system 400. In this view, a reflector 450 is depicted and can rotate about a horizontal axis. A pulse 604 can be emitted by the LiDAR at the rotating reflector 450 and can be emitted perpendicular to the horizontal axis 602. Similarly, the pulse 604 can be received by the LiDAR in a similar manner.

[0073] Although the LiDAR pulses are discussed as being perpendicular to the horizontal axis 602, it should be understood that the LiDAR pulses may be at any angle relative to the horizontal axis 602 (e.g., the reflector angle may be at any angle between 60 degrees and 120 degrees, inclusive). In various embodiments, the LiDAR transmits pulses relative to the front side (e.g., the front side 604) of the environment capture system 400 (e.g., in a direction opposite to the center of the field of view of the lens or towards the back side 606).

[0074] As discussed herein, the environment capture system 400 can rotate about the vertical axis 608. In various embodiments, the environment capture system 400 captures images and then rotates 90 degrees, such that a fourth set of images is captured when the environment capture system 400 has completed a 270-degree rotation from the original starting position from which the first set of images was captured. Thus, the environment capture system 400 can generate four sets of images over a total of 270 degrees of rotation (e.g., assuming the first set of images was captured prior to the initial rotation of the environment capture system 400). In various embodiments, the images (e.g., four sets of images) from a single sweep of the environment capture system 400 (e.g., captured in a single full rotation or 270-degree rotation about the vertical axis) together with the depth data acquired during the same sweep are sufficient to generate a 3D visualization without requiring any additional sweeps or rotations of the environment capture system 400.

[0075] It should be understood that in this example, the LiDAR pulses are emitted and directed by a rotating mirror in a position away from the rotation point of the environment capture system 400. In this example, the distance from the rotation point of the mount is 608 (e.g., the lens can be at a zero-parallax point, while the lens can be in a position behind the lens relative to the front of the environment capture system 400). Because the LiDAR pulses are directed by the mirror 450 at a position offset from the rotation point, the LiDAR cannot receive depth data from a cylinder extending from above the environment capture system 400 to below the environment capture system 400. In this example, the radius of the cylinder (e.g., a cylinder with no depth information) can be measured from the center of the rotation point of the motor mount to the point where the mirror 450 directs the LiDAR pulses.

[0076] Additionally, in Figure 6b, a cavity 610 is depicted. In this example, the environment capture system 400 includes a rotating mirror within the body of the housing of the environment capture system 400. There is a cutout section from the housing. The laser pulses can be reflected out of the housing by the mirror, and the reflection can then be received by the mirror and directed back to the LiDAR to enable the LiDAR to generate a depth signal and / or depth data. The base of the body of the environment capture system 400 below the cavity 610 can block some of the laser pulses. The cavity 610 can be defined by the base of the environment capture system 400 and the rotating mirror. As shown Figure 6B As shown, there may still be space between the edge of the angled reflector and the housing of the environment capture system 400 containing the LiDAR.

[0077] In various embodiments, the LiDAR is configured to stop emitting laser pulses if the rotational speed of the mirror drops below a rotational safety threshold (e.g., if there is a malfunction of the motor that rotates the mirror or the mirror is held in position.) In this way, the LiDAR can be configured for safety and reduce the likelihood that laser pulses will continue to be emitted in the same direction (e.g., at the user's eyes).

[0078] FIG6 b depicts a view from above the environment capture system 400 in some embodiments. In this example, the front of the environment capture system 400 is depicted, with the lens concave and directly above the center of the rotation point (e.g., above the center of the mount). The front of the camera is concave for the lens, and the front of the housing is flared to allow the image sensor's field of view to be unobstructed by the housing. The reflector 450 is depicted as pointing upward.

[0079] Figure 7 A perspective view of components of one example of an environment capture system 300, according to some embodiments, is depicted. Environment capture system 700 includes a front cover 702, a lens assembly 704, a structural frame 706, a LiDAR 708, a front housing 710, a mirror assembly 712, a GPS antenna 714, a rear housing 716, a vertical motor 718, a display 720, a battery pack 722, a mount 724, and a horizontal motor 726.

[0080] In various embodiments, the environment capture system 700 can be configured to scan, align, and generate 3D meshes outdoors in full sunlight as well as indoors. This eliminates the barriers to adoption of other systems that are indoor-only tools. The environment capture system 700 can be able to scan large spaces faster than other devices. In some embodiments, the environment capture system 700 can provide improved depth accuracy by improving single-scan depth accuracy at 90m.

[0081] In some embodiments, the environment capture system 700 may weigh at or about 1 kg. In one example, the environment capture system 700 may weigh 1-3 kg.

[0082] The front cover 702, the front housing 710 and the rear housing 716 form part of a housing. In one example, the front cover may have a width w of 75 mm.

[0083] Lens assembly 704 may include a camera lens that focuses light onto an image capture device. The image capture device can capture images of the physical environment. A user can position environment capture system 700 to capture a portion of a floor of a building (such as second building 422 in FIG. 1 ) to obtain a panoramic image of that portion of the floor. Environment capture system 700 can be moved to another portion of the floor of the building to obtain a panoramic image of another portion of the floor. In one example, the depth of field of the image capture device is 0.5 meters to infinity. Figure 8A Example lens sizes are depicted in some embodiments.

[0084] In some embodiments, the image capture device is a complementary metal oxide semiconductor (CMOS) image sensor (e.g., a Sony IMX283-20 ​​Megapixel CMOS MIPI sensor with an NVidia Jetson Nano SOM). In various embodiments, the image capture device is a charge coupled device (CCD). In one example, the image capture device is a red-green-blue (RGB) sensor. In one embodiment, the image capture device is an infrared (IR) sensor. The lens assembly 704 can provide the image capture device with a wide field of view.

[0085] Image sensors can have many different specifications. In one example, the image sensor includes the following:

[0086] Number of pixels per column Pixel 5496 Number of pixels per row Pixel 3694 Resolution MP >20 Image circle diameter mm 15.86mm Pixel pitch um 2.4um Pixels per degree (PPD) PPD >37 Chief ray angle at full height Spend 3.0° Output interface - MIPI Green Sensitivity V / lux*s >1.7 SNR (100 lux, 1x gain) dB >65 Dynamic Range dB >70

[0087] An example specification could be as follows:

[0088]

[0089] In various embodiments, when observing the MTF at F0 relative field (ie, center), the focus shift may vary from +28 microns at 0.5 m to -25 microns at infinity for a total through focus shift of 53 microns.

[0090] Figure 8B Depicted are example lens design specifications for some embodiments.

[0091] In some examples, lens assembly 704 has a HFOV of at least 148 degrees and a VFOV of at least 94 degrees. In one example, lens assembly 704 has a field of view of 150°, 180°, or within a range of 145° to 180°. In one example, image capture of a 360° view around environment capture system 700 can be obtained using three or four separate image captures from an image capture device of environment capture system 700. In various embodiments, the image capture device can have a resolution of at least 37 pixels per degree. In some embodiments, environment capture system 700 includes a lens cap (not shown) to protect lens assembly 704 when not in use. The output of lens assembly 704 can be a digital image of an area of ​​a physical environment. The images captured by lens assembly 704 can be stitched together to form a 2D panoramic image of the physical environment. A 3D panorama can be generated by combining the depth data captured by LiDAR 708 with a 2D panoramic image generated by stitching together multiple images from lens assembly 704. In some embodiments, the images captured by the environment capture system 402 are stitched together by the image processing system 406. In various embodiments, the environment capture system 402 generates a "preview" or "thumbnail" version of the 2D panoramic image. The preview or thumbnail version of the 2D panoramic image can be presented on a user system 1110, such as an iPad, a personal computer, a smartphone, etc. In some embodiments, the environment capture system 402 can generate a mini-map of the physical environment representing an area of ​​the physical environment. In various embodiments, the image processing system 406 generates a mini-map representing the area of ​​the physical environment.

[0092] The image captured by lens assembly 704 may include capture device position data identifying or indicating the capture location of the 2D image. For example, in some embodiments, the capture device position data can include Global Positioning System (GPS) coordinates associated with the 2D image. In other embodiments, the capture device position data can include position information indicating the relative position of the capture device (e.g., a camera and / or 3D sensor) relative to its environment, such as the relative or calibrated position of the capture device relative to an object in the environment, another camera in the environment, another device in the environment, etc. In some embodiments, this type of position data can be determined by a capture device associated with the capture of the image (e.g., a camera and / or a device operably coupled to the camera that includes positioning hardware and / or software) and received with the image. The placement of lens assembly 704 is not simply by design. By placing lens assembly 704 at or substantially at the center of the rotational axis, parallax effects can be reduced.

[0093] In some embodiments, the structural frame 706 holds the lens assembly 704 and the LiDAR 708 in a specific position and can help protect the components of the example environment capture system. The structural frame 706 can be used to help rigidly mount the LiDAR 708 and place the LiDAR 708 in a fixed position. In addition, the fixed position of the lens assembly 704 and the LiDAR 708 enables a fixed relationship to align depth data with image information to help generate a 3D image. The 2D image data and depth data captured in the physical environment can be aligned relative to a common 3D coordinate space to generate a 3D model of the physical environment.

[0094] In various embodiments, LiDAR 708 captures depth information of the physical environment. When a user places the environment capture system 700 on a portion of a second building's floor, LiDAR 708 can obtain depth information of objects. LiDAR 708 can include an optical sensing module capable of measuring the distance to a target or object in a scene by illuminating the target or scene with pulses from a laser and measuring the time it takes for photons to travel to the target and back to LiDAR 708. The measurements can then be transformed into a grid coordinate system using information derived from the horizontal drive train of the environment capture system 700.

[0095] In some embodiments, the LiDAR 708 can return depth data points with timestamps (of its internal clock) every 10 microseconds. The LiDAR 708 can sample a portion of the sphere (the small holes at the top and bottom) every 0.25 degrees. In some embodiments, with one data point every 10 microseconds and 0.25 degrees, each point "disc" can have 14.40 milliseconds and 1440 disks, resulting in a nominal 20.7-second sphere. Because each disk captures front-to-back, the sphere can be captured in a 180° scan.

[0096] In one example, the LiDAR 708 specifications may be as follows:

[0097]

[0098]

[0099] One advantage of utilizing LiDAR is that, in the case of lower wavelength (e.g., 905 nm, 900-940 nm, etc.) LiDAR, it can allow the environment capture system 700 to determine depth information for outdoor environments or indoor environments with bright light.

[0100] The placement of lens assembly 704 and LiDAR 708 can allow environment capture system 700 or a digital device in communication with environment capture system 700 to generate 3D panoramic images using depth data from LiDAR 708 and lens assembly 704. In some embodiments, 2D and 3D panoramic images are not generated on environment capture system 402.

[0101] The output of the LiDAR 708 may include attributes associated with each laser pulse sent by the LiDAR 708. Attributes include the intensity of the laser pulse, the number of returns, the current number of returns, the classification point, the RGC value, the GPS time, the scan angle, the scan direction, or any combination thereof. The depth of field may be (0.5 m; infinity), (1 m; infinity), etc. In some embodiments, the depth of field is 0.2 m to 1 m and infinity.

[0102] In some embodiments, while the environment capture system 700 is stationary, the environment capture system 700 captures four separate RBG images using the lens assembly 704. In various embodiments, while the environment capture system 700 is in motion, moving from one RBG image capture location to another RBG image capture location, the LiDAR 708 captures depth data in four different situations. In one example, a 360° rotation of the environment capture system 700 (which may be referred to as a sweep) is used to capture a 3D panoramic image. In various embodiments, a rotation of the environment capture system 700 less than 360° is used to capture a 3D panoramic image. The output of the sweep may be a sweep list (SWL), which includes image data from the lens assembly 704 and depth data from the LiDAR 708, as well as the properties of the sweep, including GPS location and a timestamp when the sweep occurred. In various embodiments, a single sweep (e.g., a single 360-degree rotation of the environment capture system 700) captures sufficient image and depth information to generate a 3D visualization (e.g., by a digital device in communication with the environment capture system 700, which receives image and depth data from the environment capture system 700 and uses only the image and depth data from the environment capture system 700 captured in the single sweep to produce the 3D visualization).

[0103] In some embodiments, images captured by the environment capture system 402 may be blended, stitched together, and combined with depth data from the LiDAR 708 via the image stitching and processing systems discussed herein.

[0104] In various embodiments, the environment capture system 402 and / or an application on the user system 1110 may generate a preview or thumbnail version of the 3D panoramic image. The preview or thumbnail version of the 3D panoramic image may be presented on the user system 1110 and may have a lower image resolution than the 3D panoramic image generated by the image processing system 406. After the lens assembly 704 and LiDAR 708 capture images and depth data of the physical environment, the environment capture system 402 may generate a mini-map representing an area of ​​the physical environment captured by the environment capture system 402. In some embodiments, the image processing system 406 generates the mini-map representing the area of ​​the physical environment. After capturing images and depth data of a home's living room using the environment capture system 402, the environment capture system 402 may generate an overhead view of the physical environment. The user may use this information to determine areas of the physical environment for which the user has not yet captured or generated a 3D panoramic image.

[0105] In one embodiment, the environment capture system 700 may interleave image capture by an image capture device using lens assembly 704 with depth information capture using LiDAR 708. For example, an image capture device may capture a segment 1605 of a physical environment (e.g., Figure 16 1605, and then the LiDAR 708 obtains depth information from segment 1605. Once the LiDAR 708 obtains depth information from segment 1605, the image capture device may continue to move to capture images of another segment 1610, and then the LiDAR 708 obtains depth information from segment 1610, thereby interleaving image capture and depth information capture.

[0106] In some embodiments, the LiDAR 708 may have a field of view of at least 145°, and depth information for all objects in the 360° view of the environment capture system 700 may be obtained in three or four scans by the environment capture system 700. In another example, the LiDAR 708 may have a field of view of at least 150°, 180°, or between 145° and 180°.

[0107] The increase in the field of view of the lens reduces the amount of time required to obtain visual and depth information of the physical environment surrounding the environment capture system 700. In various embodiments, the LiDAR 708 has a minimum depth range of 0.5 meters. In one embodiment, the LiDAR 708 has a maximum depth range of greater than 8 meters.

[0108] LiDAR 708 can utilize a mirror assembly 712 to direct the laser at various scanning angles. In one embodiment, an optional vertical motor 718 provides the ability to vertically move the mirror assembly 712. In some embodiments, the mirror assembly 712 can be a dielectric mirror with a hydrophobic coating or layer. The mirror assembly 712 can be coupled to a vertical motor 718, which rotates the mirror assembly 712 during use.

[0109] The reflectors of the reflector assembly 712 may, for example, include the following specifications:

[0110]

[0111] The reflectors of the reflector assembly 712 may, for example, include the following specifications for materials and coatings:

[0112]

[0113] The hydrophobic coating of the reflector of the reflector assembly 712 may, for example, include a contact angle number >105.

[0114] The reflectors of the reflector assembly 712 may include the following quality specifications:

[0115]

[0116]

[0117] The vertical motor may include, for example, the following specifications:

[0118]

[0119] Due to the RGB capture device and LiDAR 708, the environment capture system 700 can capture images outdoors in bright sunlight, or indoors with bright light or sunlight glare from windows. In systems that utilize different devices (e.g., structured light devices), they may not be able to operate in bright environments, whether indoors or outdoors. These devices are typically limited to use only indoors and only during dawn or sunset to control light. Otherwise, the bright spots in the room create artifacts or "holes" in the image that must be filled or corrected. However, the environment capture system 700 can be used both indoors and outdoors in bright sunlight. The capture device and LiDAR 708 may be able to capture image and depth data in bright environments without artifacts or holes caused by glare or bright light.

[0120] In one embodiment, the GPS antenna 714 receives Global Positioning System (GPS) data. The GPS data can be used to determine the location of the environment capture system 700 at any given time.

[0121] In various embodiments, the display 720 allows the environment capture system 700 to provide the current status of the system, such as updating, warming up, scanning, scan complete, error, etc.

[0122] The battery pack 722 provides power to the environmental capture system 700. The battery pack 722 can be removable and rechargeable, allowing the user to insert a new battery pack 722 while charging a depleted battery pack. In some embodiments, the battery pack 722 can allow for continuous use of at least 1000 SWLs or at least 250 SWLs before recharging. The environmental capture system 700 can utilize a USB-C plug for recharging.

[0123] In some embodiments, the mount 724 is a connector that provides for connecting the environment capture system 700 to a platform such as a tripod or mount. A horizontal motor 726 can rotate the environment capture system 700 about the xy plane. In some embodiments, the horizontal motor 726 can provide information to a grid coordinate system to determine the (x, y, z) coordinates associated with each laser pulse. In various embodiments, the horizontal motor 726 can enable the environment capture system 700 to scan quickly due to the wide field of view of the lens, the positioning of the lens about the axis of rotation, and the LiDAR device.

[0124] In one example, the horizontal motor 726 may have the following specifications:

[0125]

[0126] In various embodiments, the mount 724 may include a quick release adapter.The holding torque may be, for example, >2.0 Nm, and the durability of the capture operation may be up to or exceeding 70,000 cycles.

[0127] For example, the environment capture system 700 can enable the construction of a 3D mesh of a standard home where the distance between sweeps is greater than 8 meters. The time to capture, process, and align a room sweep can be under 45 seconds. In one example, the time frame from the start of the sweep capture to when the user can move the environment capture system 700 can be less than 15 seconds.

[0128] In various embodiments, these components provide the environment capture system 700 with the ability to align outdoor and indoor scan locations and thus create a seamless roaming experience between indoor and outdoor (which can be a high priority for hotels, vacation rentals, real estate, construction documentation, CRE, and as-built modeling and verification). The environment capture system 700 can also generate an "outdoor dollhouse" or outdoor mini-map. As shown herein, the environment capture system 700 can also improve the accuracy of 3D reconstruction, primarily from a measurement perspective. With respect to scan density, the ability of the user to tune it can also be a factor in advantage. These components can also enable the environment capture system 700 to capture wide empty spaces (e.g., longer ranges). In order to generate a 3D model of a wide empty space, the environment capture system may need to scan and capture 3D data and depth data from a larger range of distances than when generating a 3D model of a smaller space.

[0129] In various embodiments, these components enable the environment capture system 700 to align SWL and reconstruct 3D models in a similar manner for both indoor and outdoor use. These components can also enable the environment capture system 700 to perform geo-positioning of the 3D model (which can be easily integrated into Google Street View and help align outdoor panoramas if desired).

[0130] The image capture device of the environment capture system 700 may be capable of providing DSLR-like images with a quality printable at 8.5"x11" for a 70° VFOV and RGB image type.

[0131] In some embodiments, the environment capture system 700 can capture an RGB image using an image capture device (e.g., using a wide-angle lens) and then move the lens (using a motor for a total of four movements) before capturing the next RGB image. While the horizontal motor 726 rotates the environment capture system 90 degrees, the LiDAR 708 can capture depth data. In some embodiments, the LiDAR 708 includes an APD array.

[0132] In some embodiments, the image and depth data can then be sent to a capture application (e.g., a device in communication with the environment capture system 700, such as a smart device or an image capture system on a network). In some embodiments, the environment capture system 700 can send the image and depth data to the image processing system 406 for processing and generating a 2D panoramic image or a 3D panoramic image. In various embodiments, the environment capture system 700 can generate a sweep list of captured RGB images and depth data from a 360-degree rotation of the environment capture system 700. The sweep list can be sent to the image processing system 406 for stitching and alignment. The output of the sweep can be a SWL, which includes image data from the lens assembly 704 and depth data from the LiDAR 708, as well as the properties of the sweep, including GPS location and a timestamp when the sweep occurred.

[0133] In various embodiments, the LiDAR, vertical reflector, RGB lens, tripod mount, and horizontal drive are rigidly mounted within the housing to allow the housing to be opened without recalibrating the system.

[0134] Figure 9a A block diagram 900 of an example of an environment capture system according to some embodiments is depicted. The block diagram 900 includes a power supply 902, a power converter 904, an input / output (I / O) printed circuit board assembly (PCBA), a system-on-module (SOM) PCBA, a user interface 910, a LiDAR 912, a mirror brushless DC (BLCD) motor 914, a drive train 916, a wide FOV (WFOV) lens 918, and an image sensor 920.

[0135] The power supply 902 may be Figure 7 Battery pack 722. The power source can be a removable, rechargeable battery, such as a lithium-ion battery (e.g., 4 x 18650 lithium-ion batteries), capable of providing power to the environmental capture system.

[0136] The power converter 904 can change the voltage level from the power supply 902 to a lower or higher voltage level so that it can be utilized by the electronic components of the ambient capture system. The ambient capture system can utilize 4x 18650 lithium-ion batteries in a 4S1P configuration or four series connected and one parallel connected configuration.

[0137] In some embodiments, the I / O PCBA 906 may include components that provide an IMU, Wi-Fi, GPS, Bluetooth, an inertial measurement unit (IMU), motor drivers, and a microcontroller. In some embodiments, the I / O PCBA 906 includes a microcontroller for controlling the horizontal motor and encoding the horizontal motor control, and for controlling the vertical motor and encoding the vertical motor control.

[0138] The SOM PCBA 908 may include a central processing unit (CPU) and / or a graphics processing unit (GPU), memory, and a mobile interface. The SOM PCBA 908 may control the LiDAR 912, the image sensor 920, and the I / O PCBA 906. The SOM PCBA 908 may determine the (x, y, z) coordinates associated with each laser pulse of the LiDAR 912 and store the coordinates in a memory component of the SOM PCBA 908. In some embodiments, the SOM PCBA 908 may store the coordinates in an image processing system of the environment capture system 400. In addition to the coordinates associated with each laser pulse, the SOM PCBA 908 may also determine additional attributes associated with each laser pulse, including the intensity of the laser pulse, the number of returns, the current number of returns, the classification point, the RGC value, the GPS time, the scan angle, and the scan direction.

[0139] In some embodiments, the SOM PCBA 908 includes a Nvidia SOM PCBA w / CPU / GPU, DDR, eMMC, Ethernet.

[0140] The user interface 910 may include physical buttons or switches that a user can interact with. The buttons or switches may provide functions such as turning the environment capture system on and off, scanning the physical environment, etc. In some embodiments, the user interface 910 may include a display, such as Figure 7 Display 720.

[0141] In some embodiments, the LiDAR 912 captures depth information of the physical environment. The LiDAR 912 includes an optical sensing module that can measure the distance to a target or object in a scene by illuminating the target or scene with light using pulses from a laser. The optical sensing module of the LiDAR 912 measures the time it takes for photons to travel to the target or object and return to the receiver in the LiDAR 912 after reflection, thereby giving the LiDAR the distance from the target or object. Together with the distance, the SOM PCBA 908 can determine the (x, y, z) coordinates associated with each laser pulse. The LiDAR 912 can be assembled within a width of 58 mm, a height of 55 mm, and a depth of 60 mm.

[0142] The LiDAR 912 may include a range of 90 m (10% reflectivity), a range of 130 m (20% reflectivity), a range of 260 m (100% reflectivity), a range accuracy of 2 cm (1σ@900 m), a wavelength of 1705 nm, and a beam divergence of 0.28 x 0.03 degrees.

[0143] The SOM PCBA 908 can determine the coordinates based on the position of the drive train 916. In various embodiments, the LiDAR 912 can include one or more LiDAR devices. Multiple LiDAR devices can be used to increase LiDAR resolution.

[0144] The mirror brushless DC (BLCD) motor 914 can control Figure 7 The reflector assembly 712.

[0145] In some embodiments, the drive train 916 may include Figure 7 The horizontal motor 726 of FIG. When the environment capture system is mounted on a platform such as a tripod, the drive train 916 can provide rotation of the environment capture system. The drive train 916 can include a stepper motor Nema 14, a worm and plastic wheel drive train, a clutch, a bushing bearing, and a backlash prevention mechanism. In some embodiments, the environment capture system can be capable of completing a scan in less than 17 seconds. In various embodiments, the drive train 916 has a maximum speed of 60 degrees / second, 300 degrees / second, and a maximum speed of 100 degrees / second. 2 The encoder features a maximum acceleration of 0.5 nm, a maximum torque of 0.5 nm, an angular position accuracy of less than 0.1 degrees, and an encoder resolution of approximately 4096 counts per revolution.

[0146] In some embodiments, the drive train 916 includes a vertical monogon mirror and a motor. In this example, the drive train 916 can include a BLDC motor, an external Hall effect sensor, a magnet (paired with the Hall effect sensor), a mirror mount, and a mirror. In this example, the drive train 916 can have a maximum speed of 4,000 rpm and a maximum acceleration of 300 degrees / second^2. In some embodiments, the monogon mirror is a dielectric mirror. In one embodiment, the monogon mirror includes a hydrophobic coating or layer.

[0147] The components of the environment capture system are positioned so that the lens assembly and LiDAR are placed substantially at the center of the rotation axis. This can reduce image parallax that occurs when the image capture system is not placed at the center of the rotation axis.

[0148] In some embodiments, the WFOV lens 918 may be Figure 7704 of the lens assembly. The WFOV lens 918 focuses light onto the image capture device. In some embodiments, the WFOV lens can have a FOV of at least 145 degrees. With such a wide FOV, three separate image captures of the image capture device can be utilized to obtain image capture of a 360-degree view around the environment capture system. In some embodiments, the WFOV lens 918 can be approximately ~60 mm in diameter and ~80 mm total length to lens (TTL). In one example, the WFOV lens 918 can include a horizontal field of view greater than or equal to 148.3 degrees and a vertical field of view greater than or equal to 94 degrees.

[0149] The image capture device may include a WFOV lens 918 and an image sensor 920. The image sensor 920 may be a CMOS image sensor. In one embodiment, the image sensor 920 is a charge coupled device (CCD). In some embodiments, the image sensor 920 is a red-green-blue (RGB) sensor. In one embodiment, the image sensor 920 is an IR sensor. In various embodiments, the image capture device may have a resolution of at least 35 pixels per degree (PPD).

[0150] In some embodiments, the image capture device may include an F-number of f / 2.4, an image circle diameter of 15.86 mm, a pixel pitch of 2.4 um, an HFOV of >148.3°, a VFOV of >94.0°, pixels per degree of >38.0 PPD, a chief ray angle at full height of 3.0°, a minimum object distance of 1300 mm, a maximum object distance of infinity, a relative illumination of >130%, a maximum distortion of <90%, and a spectral transmittance variation of <=5%.

[0151] In some embodiments, the lens can include an F-number of 2.8, an image circle diameter of 15.86mm, pixels per degree >37, a chief ray angle at full height of 3.0, an L1 diameter <60mm, a TTL <80mm, and a relative illumination >50%.

[0152] The lens may include >85% of 52lp / mm (on-axis), >66% of 104lp / mm (on-axis), >45% of 1308lp / mm (on-axis), >75% of 52lp / mm (83% field), >41% of 104lp / mm (83% field) and >25% of 1308lp / mm (83% field).

[0153] The ambient capture system can have a resolution of >20MP, a green sensitivity of >1.7V / lux*s, an SNR of >65dB (100lux, 1x gain), and a dynamic range of >70dB.

[0154] Figure 9bA block diagram of an example SOM PCBA 908 of an environment capture system according to some embodiments is depicted. The SOM PCBA 908 may include a communication component 922, a LiDAR control component 924, a LiDAR position component 926, a user interface component 928, a classification component 930, a LiDAR data storage area 932, and a captured image data storage area 934.

[0155] In some embodiments, the communication component 922 can be connected to any component of the SOM PCBA 1008 and Figure 9a The environment captures the sending and receiving of requests or data between components of the system.

[0156] In various embodiments, the LiDAR control component 924 can control various aspects of the LiDAR. For example, the LiDAR control component 924 can send a control signal to the LiDAR 912 to start emitting laser pulses. The control signal sent by the LiDAR control component 924 can include instructions regarding the frequency of the laser pulses.

[0157] In some embodiments, the LiDAR position component 926 can utilize GPS data to determine the location of the environment capture system. In various embodiments, the LiDAR position component 926 utilizes the position of the mirror assembly to determine the scan angle and (x, y, z) coordinates associated with each laser pulse. The LiDAR position component 926 can also utilize an IMU to determine the orientation of the environment capture system.

[0158] The user interface component 928 can facilitate interaction between the user and the environment capture system. In some embodiments, the user interface component 928 can provide one or more user interface elements with which the user can interact. The user interface provided by the user interface component 928 can be sent to the user system 1110. For example, the user interface component 928 can provide a visual representation of an area of ​​the floor plan of a building to the user system (e.g., a digital device). When the user places the environment capture system in different parts of the floor of the building to capture and generate a 3D panoramic image, the environment capture system can generate a visual representation of the floor plan. The user can place the environment capture system in an area of ​​the physical environment to capture and generate a 3D panoramic image in that area of ​​the house. Once the 3D panoramic image of the area has been generated by the image processing system, the user interface component can update the floor plan view using the overhead view of the living room area depicted in Figure 1b. In some embodiments, the floor plan view 200 can be generated by the user system 1110 after a second sweep of the same home or floor of the building has been captured.

[0159] In various embodiments, the classification component 930 can classify the type of physical environment. The classification component 930 can analyze the objects in the image or the objects in the image to classify the type of physical environment captured by the environment capture system. In some embodiments, the image processing system can be responsible for classifying the type of physical environment captured by the environment capture system 400.

[0160] The LiDAR data store 932 can be any structure and / or multiple structures suitable for the captured LiDAR data (e.g., an active database, a relational database, a self-referential database, a table, a matrix, an array, a flat file, a document-oriented storage system, a non-relational No-SQL system, an FTS management system such as Lucene / Solar, and / or the like). The image data store 408 can store the captured LiDAR data. However, in situations where the communication network 404 is not functioning, the LiDAR data store 932 can be used to cache the captured LiDAR data. For example, in situations where the environment capture system 402 and the user system 1110 are in a remote location without a cellular network or in an area without Wi-Fi, the LiDAR data store 932 can store the captured LiDAR data until it can be transferred to the image data store 934.

[0161] Similar to the LiDAR data store, the captured image data store 934 can be any structure and / or multiple structures suitable for capturing images (e.g., an active database, a relational database, a self-referential database, a table, a matrix, an array, a flat file, a document-oriented storage system, a non-relational No-SQL system, an FTS management system such as Lucene / Solar, and / or the like). The image data store 934 can store captured images.

[0162] Figures 10a-10c Depicted is a process for an environment capture system 400 to capture images in some embodiments. Figures 10a-10c As shown, the environment capture system 400 can capture a burst of images at different exposures. A burst of images can be a group of images, each with a different exposure. The first burst of images occurs at time 0.0. The environment capture system 400 can receive the first frame and then evaluate the first frame while waiting for the second frame. Figure 10a Instructs to blend the first frame before the second frame arrives. In some embodiments, the environment capture system 400 can process each frame to identify pixels, colors, etc. Once the next frame arrives, the environment capture system 400 can process the most recently received frame and then blend the two frames together.

[0163] In various embodiments, the environment capture system 400 performs image processing to blend the sixth frame and further evaluates pixels in the blended frame (e.g., a frame that may include elements from any number of frames in the image burst). During a final step before or during movement (e.g., rotation) of the environment capture system 400, the environment capture system 400 may optionally transfer the blended image from the graphics processing unit to the CPU memory.

[0164] The process Figure 10b Continue in Figure 10b At the beginning, the environment capture system 400 takes another burst. The environment capture system 400 can use JxR to compress the blended frame and / or capture all or part of the frame. Figure 10a , a burst of images can be a group of images, each with a different exposure (the exposure length of each frame of the group can be different from Figure 10a and 10c ). The second image burst occurs at time 2 seconds. The environment capture system 400 can receive the first frame and then evaluate the first frame while waiting for the second frame. Figure 10b Instructs to blend the first frame before the second frame arrives. In some embodiments, the environment capture system 400 can process each frame to identify pixels, colors, etc. Once the next frame arrives, the environment capture system 400 can process the most recently received frame and then blend the two frames together.

[0165] In various embodiments, the environment capture system 400 performs image processing to blend the sixth frame and further evaluates pixels in the blended frame (e.g., a frame that may include elements from any number of frames in the image burst). During a final step before or during movement (e.g., rotation) of the environment capture system 400, the environment capture system 400 may optionally transfer the blended image from the graphics processing unit to the CPU memory.

[0166] After the rotation, the environment capture system 400 may continue the process by taking another color burst at approximately time 3.5 seconds (e.g., after the 180 degree rotation). The environment capture system 400 may use JxR to compress the blended frame and / or capture all or part of the frame. The burst of images may be a group of images, each image having a different exposure (the exposure length of each frame of the group may be different from the exposure length of the frame). Figure 10a and 10c The environment capture system 400 may receive the first frame and then evaluate the first frame while waiting for the second frame. Figure 10bInstructs to blend the first frame before the second frame arrives. In some embodiments, the environment capture system 400 can process each frame to identify pixels, colors, etc. Once the next frame arrives, the environment capture system 400 can process the most recently received frame and then blend the two frames together.

[0167] In various embodiments, the environment capture system 400 performs image processing to blend the sixth frame and further evaluates pixels in the blended frame (e.g., a frame that may include elements from any number of frames in the image burst). During a final step before or during movement (e.g., rotation) of the environment capture system 400, the environment capture system 400 may optionally transfer the blended image from the graphics processing unit to the CPU memory.

[0168] exist Figure 10c The last burst occurs at time 5 seconds. The environment capture system 400 can use JxR to compress the blended frames and / or capture all or part of the frames. A burst of images can be a group of images, each with a different exposure (the exposure length of each frame of the group can be different from the total exposure length of the frame). Figure 10a and 10b The environment capture system 400 may receive the first frame and then evaluate the first frame while waiting for the second frame. Figure 10c Instructs to blend the first frame before the second frame arrives. In some embodiments, the environment capture system 400 can process each frame to identify pixels, colors, etc. Once the next frame arrives, the environment capture system 400 can process the most recently received frame and then blend the two frames together.

[0169] In various embodiments, the environment capture system 400 performs image processing to blend the sixth frame and further evaluates pixels in the blended frame (e.g., a frame that may include elements from any number of frames in the image burst). During a final step before or during movement (e.g., rotation) of the environment capture system 400, the environment capture system 400 may optionally transfer the blended image from the graphics processing unit to the CPU memory.

[0170] The dynamic range of an image capture device is a measure of how much light an image sensor can capture. Dynamic range is the difference between the darkest and brightest areas of an image. There are many ways to increase the dynamic range of an image capture device, one of which is to capture multiple images of the same physical environment using different exposures. Images captured with short exposures will capture brighter areas of the physical environment, while long exposures will capture darker areas of the physical environment. In some embodiments, the environment capture system can capture multiple images with six different exposure times. Some or all of the images captured by the environment capture system are used to generate a 2D image with high dynamic range (HDR). One or more of the captured images can be used for other functions, such as ambient light detection, flicker detection, etc.

[0171] A 3D panoramic image of a physical environment can be generated based on four separate image captures by an image capture device and four separate depth data captures by a LiDAR device of an environment capture system. Each of the four separate image captures can include a series of image captures with different exposure times. A blending algorithm can be used to blend the series of image captures with different exposure times to generate one of four RGB image captures, which can be used to generate a 2D panoramic image. For example, the environment capture system can be used to capture a 3D panoramic image of a kitchen. The image of one wall of the kitchen may include a window, and the image with the image captured with a shorter exposure may provide a view outside the window, but may underexpose the rest of the kitchen. Conversely, another image captured with a longer exposure may provide a view inside the kitchen. The blending algorithm can generate a blended RGB image by blending the view outside the kitchen window from one image with the rest of the kitchen view from another image.

[0172] In various embodiments, a 3D panoramic image can be generated based on three separate image captures by an image capture device and four separate depth data captures by a LiDAR device of an environment capture system. In some embodiments, the number of image captures and the number of depth data captures can be the same. In another embodiment, the number of image captures and the number of depth data captures can be different.

[0173] After capturing the first of a series of images with an exposure time, the blending algorithm receives the first of the series of images, calculates initial intensity weights for the image, and sets the image as a baseline image for combining subsequently received images. In some embodiments, the blending algorithm can utilize a graphics processing unit (GPU) image processing routine, such as a "blend_kernel" routine. The blending algorithm can receive subsequent images that can be blended with previously received images. In some embodiments, the blending algorithm can utilize a variation of the Blend_Kernel GPU image processing routine.

[0174] In one embodiment, the blending algorithm utilizes other methods of blending multiple images, such as determining the difference between the darkest and lightest portions of the baseline image, or the contrast of the baseline image, to determine whether the baseline image may be overexposed or underexposed. For example, a contrast value less than a predetermined contrast threshold means that the baseline image is overexposed or underexposed. In one embodiment, the contrast of the baseline image can be calculated by taking the average of the light intensity of an image or a subset of the images. In some embodiments, the blending algorithm calculates the average light intensity for each row or column of the image. In some embodiments, the blending algorithm can determine a histogram for each image received from the image capture device and analyze the histogram to determine the light intensity of the pixels that make up each image.

[0175] In various embodiments, blending can involve sampling colors within two or more images of the same scene, including along objects and seams. If there is a significant difference in color between the two images (e.g., within a predetermined threshold of color, hue, brightness, saturation, and / or similar amounts), a blending module (e.g., on the environment capture system 400 or the user device 1110) can blend the two images for a predetermined size along the location where the difference exists. In some embodiments, the greater the difference in color or image at a location in the image, the greater the amount of space around or near that location that can be blended.

[0176] In some embodiments, after blending, a blending module (e.g., on the environment capture system 400 or the user device 1110) may rescan and sample the colors along the image(s) to determine if there are other differences in the images or colors that exceed a predetermined threshold value for color, hue, brightness, saturation, and / or the like. If so, the blending module may identify the portion within the image(s) and continue blending that portion of the image. The blending module may continue resampling the images along the seam until there are no more portions of the images to blend (e.g., any differences in color are below the predetermined threshold(s)).

[0177] Figure 11 A block diagram depicts an example environment 1100 capable of capturing and stitching images to form a 3D visualization in accordance with some embodiments. The example environment 1100 includes a 3D and panoramic capture and stitching system 1102, a communication network 1104, an image stitching and processor system 1106, an image data storage area 1108, a user system 1110, and a first scene 1112 of a physical environment. The 3D and panoramic capture and stitching system 1102 and / or the user system 1110 may include an image capture device (e.g., environment capture system 400) that can be used to capture images of an environment (e.g., physical environment 1112).

[0178] The 3D and panoramic capture and stitching system 1102 and the image stitching and processor system 1106 can be part of the same system (e.g., part of one or more digital devices) that is communicatively coupled to the environment capture system 400. In some embodiments, one or more functions of the components of the 3D and panoramic capture and stitching system 1102 and the image stitching and processor system 1106 can be performed by the environment capture system 400. Similarly or alternatively, the 3D and panoramic capture and stitching system 1102 and the image stitching and processor system 1106 can be performed by the user system 1110 and / or the image stitching and processor system 1106.

[0179] The user can utilize the 3D panoramic capture and stitching system 1102 to capture multiple 2D images of an environment, such as a building interior and / or a building exterior. For example, the user can utilize the 3D and panoramic capture and stitching system 1102 to capture multiple 2D images of a first scene of the physical environment 1112 provided by the environment capture system 400. The 3D and panoramic capture and stitching system 1102 can include an alignment and stitching system 1114. Alternatively, the user system 1110 can include the alignment and stitching system 1114.

[0180] The alignment and stitching system 1114 can be software, hardware, or a combination of both, configured to provide guidance to a user of an image capture system (e.g., on the 3D and panoramic capture and stitching system 1102 or the user system 1110) and / or process images to enable the creation of an improved panoramic picture (e.g., by stitching, aligning, cropping, etc.). The alignment and stitching system 1114 can be on a computer-readable medium (described herein). In some embodiments, the alignment and stitching system 1114 can include a processor for performing the functions.

[0181] An example of a first scene of a physical environment 1112 may be any room, real estate, etc. (e.g., a representation of a living room). In some embodiments, the 3D and panoramic capture and stitching system 1102 is used to generate a 3D panoramic image of an indoor environment. In some embodiments, the 3D panoramic capture and stitching system 1102 may be a system for capturing and stitching a 3D panoramic image of an indoor environment. Figure 4 Environmental capture system 400 discussed.

[0182] In some embodiments, the 3D panoramic capture and stitching system 1102 can communicate with devices and software used to capture images and depth data, such as the environment capture system 400. All or part of the software can be installed on the 3D panoramic capture and stitching system 1102, the user system 1110, the environment capture system 400, or both. In some embodiments, a user can interact with the 3D and panoramic capture and stitching system 1102 via the user system 1110.

[0183] The 3D and panoramic capture and stitching system 1102 or the user system 1110 may obtain multiple 2D images. The 3D and panoramic capture and stitching system 1102 or the user system 1110 may obtain depth data (eg, from a LiDAR device, etc.).

[0184] In various embodiments, an application on the user system 1110 (e.g., the user's smart device, such as a smartphone or tablet) or an application on the environment capture system 400 can provide visual or audio guidance to the user for capturing images using the environment capture system 400. Graphical guidance can include, for example, floating arrows on a display of the environment capture system 400 (e.g., on a viewfinder or LED screen on the back of the environment capture system 400) to guide the user where to position and / or point the image capture device. In another example, the application can provide audio guidance on where to position and / or point the image capture device.

[0185] In some embodiments, guidance can allow a user to capture multiple images of a physical environment without the aid of a stable platform (e.g., a tripod). In one example, the image capture device can be a personal device such as a smartphone, tablet, media tablet, laptop, etc. The application can provide directions about the location for each sweep to approximate a parallax-free point based on the location of the image capture device, location information from the image capture device, and / or previous images of the image capture device.

[0186] In some embodiments, visual and / or auditory guidance enables capturing images that can be stitched together to form a panorama without requiring a tripod and without requiring camera positioning information (e.g., an indication of the position, location, and / or orientation of the camera from a sensor, GPS device, etc.).

[0187] The alignment and stitching system 1114 may align or stitch 2D images (eg, captured by the user system 1110 or the 3D panoramic capture and stitching system 1102 ) to obtain a 2D panoramic image.

[0188] In some embodiments, the alignment and stitching system 1114 utilizes a machine learning algorithm to align or stitch the multiple 2D images into a 2D panoramic image. Parameters of the machine learning algorithm can be managed by the alignment and stitching system 1114. For example, the 3D and panoramic capture and stitching system 1102 and / or the alignment and stitching system 1114 can identify objects within the 2D images to help align the images into a 2D panoramic image.

[0189] In some embodiments, the alignment and stitching system 1114 can utilize the depth data and the 2D panoramic image to obtain a 3D panoramic image. The 3D panoramic image can be provided to the 3D and panoramic stitching system 1102 or the user system 1110. In some embodiments, the alignment and stitching system 1114 determines a 3D / depth measurement associated with an identified object within the 3D panoramic image and / or sends one or more 2D images, the depth data, the 2D panoramic image(s), or the 3D panoramic image(s) to the image stitching and processor system 106 to obtain a 2D panoramic image or a 3D panoramic image having a greater pixel resolution than the 2D panoramic image or the 3D panoramic image provided by the 3D and panoramic capture and stitching system 1102.

[0190] The communication network 1104 can represent one or more computer networks (e.g., LANs, WANs, etc.) or other transmission media. The communication network 1104 can provide communication between the systems 1102, 1106-1110, and / or other systems described herein. In some embodiments, the communication network 1104 includes one or more digital devices, routers, cables, buses, and / or other network topologies (e.g., meshes, etc.). In some embodiments, the communication network 1104 can be wired and / or wireless. In various embodiments, the communication network 1104 can include the Internet, one or more wide area networks (WANs) or local area networks (LANs), one or more networks that can be public, private, IP-based, non-IP-based, etc.

[0191] The image stitching and processing system 1106 can process 2D images captured by an image capture device (e.g., the environment capture system 400 or a user device such as a smartphone, personal computer, media tablet, etc.) and stitch them into a 2D panoramic image. The 2D panoramic image processed by the image stitching and processing system 106 can have a higher pixel resolution than the panoramic image obtained by the 3D and panoramic capture and stitching system 1102.

[0192] In some embodiments, the image stitching and processing system 1106 receives and processes the 3D panoramic image to generate a 3D panoramic image having a higher pixel resolution than the pixel resolution of the received 3D panoramic image. The higher pixel resolution panoramic image can be provided to an output device, such as a computer screen, a projector screen, etc., having a higher screen resolution than the user system 1110. In some embodiments, the higher pixel resolution panoramic image can provide the output device with a more detailed panoramic image and can be magnified.

[0193] Image data store 1108 may be any structure and / or structures suitable for storing captured image and / or depth data (e.g., an active database, a relational database, a self-referential database, a table, a matrix, an array, a flat file, a document-oriented storage system, a non-relational No-SQL system, an FTS management system such as Lucene / Solar, and / or the like). Image data store 1108 may store images captured by an image capture device of user system 1110. In various embodiments, image data store 1108 stores depth data captured by one or more depth sensors of user system 1110. In various embodiments, image data store 1108 stores properties associated with an image capture device or properties associated with each of multiple image captures or depth captures used to determine a 2D or 3D panoramic image. In some embodiments, image data store 1108 stores a panoramic 2D or 3D image. The 2D or 3D panoramic image may be determined by 3D and panoramic capture and stitching system 1102 or image stitching and processor system 106.

[0194] The user system 1110 can communicate between the user and other associated systems. In some embodiments, the user system 1110 can be or include one or more mobile devices (e.g., smart phones, cellular phones, smart watches, etc.).

[0195] The user system 1110 may include one or more image capture devices, which may include, for example, an RGB camera, an HDR camera, a video camera, an IR camera, and the like.

[0196] The 3D and panoramic capture and stitching system 1102 and / or the user system 1110 may include two or more capture devices that may be arranged on or within the same mobile housing in positions relative to each other such that their collective field of view spans up to 360°. In some embodiments, paired image capture devices capable of generating stereoscopic image pairs (e.g., with slightly offset but partially overlapping fields of view) may be used. The user system 1110 may include two image capture devices with vertically stereoscopic offset fields of view capable of capturing vertical stereoscopic image pairs. In another example, the user system 1110 may include two image capture devices with vertically stereoscopic offset fields of view capable of capturing vertical stereoscopic image pairs.

[0197] In some embodiments, the user system 1110, the environment capture system 400, or the 3D and panoramic capture and stitching system 1102 can generate and / or provide image capture position and orientation information. For example, the user system 1110 or the 3D and panoramic capture and stitching system 1102 can include an inertial measurement unit (IMU) to assist in determining position data associated with one or more image capture devices that capture the plurality of 2D images. The user system 1110 can include a global positioning sensor (GPS) to provide GPS coordinate information associated with the plurality of 2D images captured by the one or more image capture devices.

[0198] In some embodiments, the user can interact with the alignment and stitching system 1114 using a mobile application installed on the user system 1110. The 3D and panoramic capture and stitching system 1102 can provide images to the user system 1110. The user can view images and previews using the alignment and stitching system 1114 on the user system 1110.

[0199] In various embodiments, the alignment and stitching system 1114 may be configured to provide or receive one or more 3D panoramic images from the 3D and panoramic capture and stitching system 1102 and / or the image stitching and processor system 1106. In some embodiments, the 3D and panoramic capture and stitching system 1102 may provide the user system 1110 with a visual representation of a portion of a floor plan of a building that has been captured by the 3D and panoramic capture and stitching system 1102.

[0200] The user of system 1110 can navigate the space around the area and view different rooms of the house. In some embodiments, as image stitching and processor system 1106 completes the generation of the 3D panoramic image, the user of user system 1110 can display the 3D panoramic image, such as the example 3D panoramic image. In various embodiments, user system 1110 generates a preview or thumbnail of the 3D panoramic image. The preview 3D panoramic image may have a lower image resolution than the 3D panoramic image generated by 3D and panoramic capture and stitching system 1102.

[0201] Figure 12 1 is a block diagram of an example of an alignment and stitching system 1114 according to some embodiments. The alignment and stitching system 1114 includes a communication module 1202, an image capture location module 1204, a stitching module 1206, a cropping module 1208, a graph cutting module 1210, a blending module 1211, a 3D image generator 1214, a captured 2D image data store 1216, a 3D panoramic image data store 1218, and a guidance module 220. It will be appreciated that any number of modules of the alignment and stitching system 1114 may be present to perform one or more of the different functions described herein.

[0202] In some embodiments, the alignment and stitching system 1114 includes an image capture module configured to receive images from one or more image capture devices (e.g., cameras). The alignment and stitching system 1114 may also include a depth module configured to receive depth data from a depth device such as LiDAR (if available).

[0203] The communication module 1202 can communicate with any module or data storage area of ​​the alignment and stitching system 1114. Figure 11 1100. Similarly, the alignment and stitching system 1114 can send and receive requests, images, or data to and from any device or system on the communication network 1104.

[0204] In some embodiments, the image capture location module 1204 can determine image capture device location data for an image capture device (e.g., a camera, which can be a standalone camera, a smartphone, a media tablet, a laptop, etc.). The image capture device location data can indicate the position and orientation of the image capture device and / or lens. In one example, the image capture location module 1204 can utilize the IMU of the user system 1110, a camera, a digital device with a camera, or the 3D and panoramic capture and stitching system 1102 to generate the image capture device location data. The image capture location module 1204 can determine the current direction, angle, or tilt of one or more image capture devices (or lenses). The image capture location module 1204 can also utilize the GPS of the user system 1110 or the 3D and panoramic capture and stitching system 1102.

[0205] For example, when a user wants to use user system 1110 to capture a 360° view of a physical environment (such as a living room), the user can hold user system 1110 in front of them at eye level to begin capturing one of multiple images that will eventually become a 3D panoramic image. To reduce the amount of parallax in the images and capture images that are more suitable for stitching and generating a 3D panoramic image, it may be preferable if one or more image capture devices are rotated at the center of the rotation axis. The alignment and stitching system 1114 can receive position information (e.g., from an IMU) to determine the position of the image capture device or lens. The alignment and stitching system 1114 can receive and store the field of view of the lens. The guidance module 1220 can provide visual and / or audio information regarding a recommended initial position for the image capture device. The guidance module 1220 can make recommendations for positioning the image capture device for subsequent images. In one example, the guidance module 1220 can provide guidance to the user to rotate and position the image capture device so that the image capture device rotates near the center of rotation. Additionally, the guidance module 1220 may provide guidance to the user to rotate and position the image capture device so that subsequent images are substantially aligned based on the field of view and / or characteristics of the image capture device.

[0206] Guidance module 1220 can provide visual guidance to the user. For example, guidance module 1220 can place markers or arrows in a viewer or display on user system 1110 or 3D and panoramic capture and stitching system 1102. In some embodiments, user system 1110 can be a smartphone or tablet computer with a display. When taking one or more pictures, guidance module 1220 can position one or more markers (e.g., different colored markers or the same marker) on an output device and / or in a viewfinder. The user can then use the markers on the output device and / or viewfinder to align the next image.

[0207] There are many techniques for guiding a user of the user system 1110 or the 3D and panoramic capture and stitching system 1102 to capture multiple images to facilitate stitching the images into a panorama. Once a panorama is derived from the multiple images, the images can be stitched together. To improve the time, efficiency, and effectiveness of stitching the images together while reducing the need to correct for artifacts or misalignments, the image capture position module 1204 and the guidance module 1220 can help the user capture the multiple images in a position that improves the quality, time efficiency, and effectiveness of stitching the images of the desired panorama.

[0208] For example, after taking the first picture, the display of user system 1110 may include two or more objects, such as circles. The two circles may appear stationary relative to the environment, and the two circles may move with user system 1110. When the two stationary circles are aligned with the two circles moving with user system 1110, the image capture device and / or user system 1110 may be aligned for the next image.

[0209] In some embodiments, after the image capture device captures an image, the image capture position module 1204 can obtain sensor measurements of the position of the image capture device (e.g., including orientation, tilt, etc.). The image capture position module 1204 can determine one or more edges of the captured image by calculating the positions of the edges of the field of view based on the sensor measurements. Additionally or alternatively, the image capture position module 1204 can determine one or more edges of the image by scanning the image captured by the image capture device, identifying objects within the image (e.g., using a machine learning model as discussed herein), determining one or more edges of the image, and positioning an object (e.g., a circle or other shape) at an edge of a display on the user system 1110.

[0210] The image capture position module 1204 can display two objects within the display of the user system 1110 that indicate the location of the field of view for the next picture. These two objects can indicate the location in the environment where the edge of the last image is located. The image capture position module 1204 can continue to receive sensor measurements of the position of the image capture device and calculate two additional objects in the field of view. The two additional objects can be spaced apart by the same width as the first two objects. Although the first two objects can represent the edges of the captured image (e.g., the rightmost edge of the image), the next two additional objects representing the edges of the field of view can be on the opposite edge (e.g., the leftmost edge of the field of view). By having the user physically align the first two objects on the edge of the image with the other two objects on the opposite edge of the field of view, the image capture device can be positioned so that another image that can be stitched together more efficiently can be captured without a tripod. This process can continue for each image until the user determines that the desired panorama has been captured.

[0211] Although multiple objects are discussed herein, it should be understood that the image capture location module 1204 can calculate the location of one or more objects for positioning the image capture device. The object can be any shape (e.g., a circle, an oval, a square, an emoji, an arrow, etc.). In some embodiments, the object can have different shapes.

[0212] In some embodiments, there may be a distance between objects representing the edge of a captured image, and there may be a distance between objects in the field of view. The user may be directed to move forward to move away so that sufficient distance can exist between the objects. Alternatively, as the image capture device approaches the correct position (e.g., by moving closer or further away from a position that will enable the next image to be taken in a position that will improve image stitching), the size of the objects in the field of view may change to match the size of the objects representing the edge of the captured image.

[0213] In some embodiments, the image capture location module 1204 can use objects in the image captured by the image capture device to estimate the location of the image capture device. For example, the image capture location module 1204 can use GPS coordinates to determine the geographic location associated with the image. The image capture location module 1204 can use this location to identify a landmark that can be captured by the image capture device.

[0214] Image capture location module 1204 may include a 2D machine learning model that converts a 2D image into a 2D panoramic image. Image capture location module 1204 may include a 3D machine learning model that converts a 2D image into a 3D representation. In one example, the 3D representation may be used to display a three-dimensional tour or visualization of the interior and / or exterior environment.

[0215] A 2D machine learning model can be trained to stitch or help stitch together two or more 2D images to form a 2D panoramic image. The 2D machine learning model can be, for example, a neural network trained with 2D images that include physical objects in the image and object recognition information that trains the 2D machine learning model to recognize objects in subsequent 2D images. Objects in the 2D image can help determine (one or more) locations within the 2D image to help determine edges of the 2D image, distortions in the 2D image, and to help align the images. Additionally, objects in the 2D image can help determine artifacts in the 2D image, blending of artifacts or boundaries between two images, locations of cut images, and / or cropped images.

[0216] In some embodiments, the 2D machine learning model can be, for example, a neural network trained with 2D images, wherein the 2D images include depth information of the environment (e.g., from a LiDAR device or structured light device of the user system 1110 or the 3D and panoramic capture and stitching system 1102) and physical objects in the images to identify the physical objects, their locations, and / or the location of the image capture device / field of view. The 2D machine learning model can identify the depth of the physical objects and other aspects of the physical objects relative to the 2D images to help align and position the two 2D images for stitching (or stitching the two 2D images).

[0217] The 2D machine learning model may include any number of machine learning models (e.g., any number of models generated by a neural network, etc.).

[0218] The 2D machine learning model may be stored on the 3D and panoramic capture and stitching system 1102, the image stitching and processor system 1106, and / or the user system 1110. In some embodiments, the 2D machine learning model may be trained by the image stitching and processor system 1106.

[0219] The image capture position module 1204 can estimate the position of the image capture device (the position of the field of view of the image capture device) based on the seams between two or more 2D images from the stitching module 1206, the image warping from the cropping module 1208 and / or the graph cut from the graph cut module 1210.

[0220] The stitching module 1206 can combine two or more 2D images to generate a 2D panorama having a larger field of view than each of the two or more images based on a seam between the two or more 2D images from the stitching module 1206, image warping and / or graphic cutting from the cropping module 1208.

[0221] The stitching module 1206 can be configured to align or "stitch together" two different 2D images that provide different perspectives of the same environment to generate a panoramic 2D image of the environment. For example, the stitching module 1206 can use known or derived (e.g., using the techniques described herein) information about the capture position and orientation of the respective 2D images to help stitch the two images together.

[0222] The stitching module 1206 may receive two 2D images. The first 2D image may have been captured immediately before or within a predetermined time period of the second image. In various embodiments, the stitching module 1206 may receive positioning information of the image capture device associated with the first image and then receive positioning information associated with the second image. The positioning information may be associated with the image based on positioning data from an IMU, GPS, and / or information provided by a user at the time the image was captured.

[0223] In some embodiments, the stitching module 1206 can utilize a 2D machine learning module to scan two images to identify objects within the two images, including objects (or portions of objects) that may be shared by the two images. For example, the stitching module 1206 can identify corners, patterns on walls, furniture, etc. that are shared at opposite edges of the two images.

[0224] The stitching module 1206 can align the edges of the two 2D images based on the positioning of the shared object (or portion of the object), positioning data from the IMU, positioning data from the GPS, and / or information provided by the user, and then combine the two edges of the images (i.e., "stitch" them together). In some embodiments, the stitching module 1206 can identify a portion of the two 2D images that overlap each other and stitch the images at the overlapping location (e.g., using the positioning data and / or the results of the 2D machine learning model).

[0225] In various embodiments, a 2D machine learning model can be trained to combine or stitch two edges of an image using positioning data from an IMU, positioning data from a GPS, and / or information provided by a user. In some embodiments, a 2D machine learning model can be trained to identify common objects in two 2D images to align and position the 2D images, and then combine or stitch two edges of the images. In other embodiments, a 2D machine learning model can be trained to use positioning data and object recognition to align and position the 2D images, and then stitch two edges of the images together to form all or part of a panoramic 2D image.

[0226] The stitching module 1206 can utilize depth information of the respective images (eg, pixels in the respective images, objects in the respective images, etc.) to facilitate aligning the respective 2D images with each other in association with generating a single 2D panoramic image of the environment.

[0227] Cropping module 1208 can address the issue of two or more 2D images when the image capture device does not remain in the same position when capturing the 2D images. For example, a user may position user system 1110 in a vertical position while capturing an image. However, while capturing another image, the user may position the user system at an angle. The resulting images may be misaligned and may exhibit parallax effects. Parallax effects occur when foreground and background objects are not aligned in the same manner in the first and second images.

[0228] The cropping module 1208 can utilize a 2D machine learning model (by applying positioning information, depth information, and / or object recognition) to detect changes in the position of the image capture device in two or more images, and then measure the amount of change in the position of the image capture device. The cropping module 1208 can warp one or more 2D images so that when the images are stitched together, the images can be aligned together to form a panoramic image while preserving certain characteristics of the images, such as keeping straight lines straight.

[0229] The output of the cropping module 1208 may include the number of pixel columns and rows to offset each pixel of the image to straighten the image. The offset amount for each image may be output in the form of a matrix indicating the number of pixel columns and rows to offset each pixel of the image.

[0230] In some embodiments, the cropping module 1208 can determine the amount of image distortion to be performed on one or more of the multiple 2D images captured by the image capture device of the user system 1110 based on one or more image capture positions from the image capture position module 1204 or gaps between two or more 2D images from the stitching module 1206, graphic cuts from the graphic cut module 1210, or blending of colors from the blending module 1211.

[0231] The graphic cut module 1210 can determine where to cut or slice one or more 2D images captured by the image capture device. For example, the graphic cut module 1210 can use a 2D machine learning model to identify objects in two images and determine that they are the same object. The image capture position module 1204, the cropping module 1208 and / or the graphic cut module 1210 can determine that the two images cannot be aligned even after being distorted. The graphic cut module 1210 can use information from the 2D machine learning model to identify segments of the two images that can be stitched together (e.g., by cutting off a portion of one or both images to aid alignment and positioning). In some embodiments, the two 2D images may overlap with at least a portion of the physical world represented in the images. The graphic cut module 1210 can identify objects in the two images, such as the same chair. However, even after the image capture positioning and image warping by the cropping module 1208, the images of the chair cannot be aligned to generate an undistorted panorama and will not correctly represent a portion of the physical world. The graphic cutting module 1210 can select one of the two images of the chair as the correct representation (e.g., based on misalignment, positioning, and / or artifacts of one image when compared to the other image) and cut the chair from the image with the misalignment, positioning error, and / or artifacts. The stitching module 1206 can then stitch the two images together.

[0232] The graphic cut module 1210 may try two combinations, for example, cutting an image of a chair from a first image and stitching the first image minus the chair to a second image, to determine which graphic cut generates a more accurate panoramic image. The output of the graphic cut module 1210 may be a location where one or more of the plurality of 2D images corresponding to the graphic cut are cut, which generates a more accurate panoramic image.

[0233] The graphic cutting module 1210 can determine how to cut or slice one or more 2D images captured by the image capture device based on one or more image capture positions from the image capture position module 1204, the stitching or seams between two or more 2D images from the stitching module 1206, the image distortion from the cropping module 1208, and the graphic cutting from the graphic cutting module 1210.

[0234] The blending module 1211 can colorize at the seam (e.g., stitching) between two images so that the seam is not visible. Variations in lighting and shading can cause the same object or surface to be output in slightly different colors or shadings. The blending module can determine the desired amount of color blending based on one or more of the image capture position from the image capture position module 1204, the stitching, the image color along the seam from the two images, the image warping from the cropping module 1208, and / or the graphic cut from the graphic cut module 1210.

[0235] In various embodiments, blending module 1211 may receive a panoramic image from a combination of two 2D images and then sample colors along the seam between the two 2D images. Blending module 1211 may receive seam location information from image capture location module 1204 to enable blending module 1211 to sample colors along the seam and determine differences. If there is a significant difference in color along the seam between the two images (e.g., within a predetermined threshold of color, hue, brightness, saturation, and / or the like), blending module 1211 may blend the two images at a predetermined size along the seam at the location where the difference exists. In some embodiments, the greater the difference in color or image along the seam, the greater the amount of space along the seam between the two images that can be blended.

[0236] In some embodiments, after blending, the blending module 1211 may rescan and sample the colors along the seam to determine if there are other differences in the images or colors that exceed a predetermined threshold value for color, hue, brightness, saturation, and / or the like. If so, the blending module 1211 may identify the portion along the seam and continue blending that portion of the image. The blending module 1211 may continue resampling the image along the seam until there are no more portions of the image to blend (e.g., any differences in color are below a predetermined threshold).

[0237] The 3D image generator 1214 can receive a 2D panoramic image and generate a 3D representation. In various embodiments, the 3D image generator 1214 uses a 3D machine learning model to transform the 2D panoramic image into a 3D representation. The 3D machine learning model can be trained using the 2D panoramic image and depth data (e.g., from a LiDAR sensor or structured light device) to generate the 3D representation. The 3D representation can be tested and reviewed for curation / screening and feedback. In some embodiments, the 3D machine learning model can be used together with the 2D panoramic image and depth data to generate the 3D representation.

[0238] In various embodiments, the accuracy, rendering speed, and quality of the 3D representations generated by the 3D image generator 1214 are greatly improved by utilizing the systems and methods described herein. For example, by rendering a 3D representation from a 2D panoramic image that has been aligned, positioned, and stitched using the methods described herein (e.g., through alignment and positioning information provided by the hardware, through improved positioning caused by guidance provided to the user during image capture, by cropping and changing the distortion of the image, by cutting the image to avoid artifacts and overcome distortion, by blending images, and / or any combination), the accuracy, rendering speed, and quality of the 3D representation are improved. Furthermore, it should be understood that by utilizing 2D panoramic images that have been aligned, positioned, and stitched using the methods described herein, the training of 3D machine learning models can be greatly improved (e.g., in terms of speed and accuracy). Furthermore, in some embodiments, the 3D machine learning model can be smaller and less complex due to the reduction in processing and learning that will be used to overcome misalignment, positioning errors, distortions, poor image cutting, poor blending, artifacts, etc. to generate a reasonably accurate 3D representation.

[0239] The trained 3D machine learning model may be stored in the 3D and panoramic capture and stitching system 1102 , the image stitching and processor system 106 , and / or the user system 1110 .

[0240] In some embodiments, the 3D machine learning model may be trained using multiple 2D images and depth data from the image capture device of the user system 1110 and / or the 3D and panoramic capture and stitching system 1102. Additionally, the 3D image generator 1214 may be trained using image capture position information associated with each of the multiple 2D images from the image capture position module 1204, the locations of seams for aligning or stitching each of the multiple 2D images from the stitching module 1206, the pixel offset(s) for each of the multiple 2D images from the cropping module 1208, and / or the graph cuts from the graph cut module 1210. In some embodiments, the 3D machine learning model can be used with the 2D panoramic image, depth data, image capture position information associated with each of the multiple 2D images from the image capture position module 1204, the seam locations of each of the multiple 2D images from the stitching module 1206, the pixel (one or more) offsets of each of the multiple 2D images from the cropping module 1208, and / or the graphic cuts from the graphic cut module 1210 to generate a 3D representation.

[0241] The stitching module 1206 may be part of a 3D model that converts multiple 2D images into a 2D panoramic or 3D panoramic image. In some embodiments, the 3D model is a machine learning algorithm, such as a predictive neural network model from 2D to 3D. The cropping module 1208 may be part of a 3D model that converts multiple 2D images into a 2D panoramic or 3D panoramic image. In some embodiments, the 3D model is a machine learning algorithm, such as a predictive neural network model from 2D to 3D. The graphic cutting module 1210 may be part of a 3D model that converts multiple 2D images into a 2D panoramic or 3D panoramic image. In some embodiments, the 3D model is a machine learning algorithm, such as a predictive neural network model from 2D to 3D. The blending module 1211 may be part of a 3D machine learning model that converts multiple 2D images into a 2D panoramic or 3D panoramic image. In some embodiments, the 3D model is a machine learning algorithm, such as a predictive neural network model from 2D to 3D.

[0242] The 3D image generator 1214 can generate a weight for each of the image capture location module 1204, the cropping module 1208, the graph cut module 1210, and the blending module 1211, which can represent the reliability or "strength" or "weakness" of the module. In some embodiments, the sum of the weights of the modules is equal to 1.

[0243] In the event that depth data is not available for multiple 2D images, the 3D image generator 1214 can determine depth data for one or more objects in the multiple 2D images captured by the image capture device of the user system 1110. In some embodiments, the 3D image generator 1214 can derive depth data based on images captured by a stereo image pair. Rather than determining depth data based on a passive stereo algorithm, the 3D image generator can evaluate the stereo image pair to determine data regarding the quality of photometric matching between the images at various depths (a more intermediate result).

[0244] The 3D image generator 1214 may be part of a 3D model that converts multiple 2D images into a 2D panorama or 3D panoramic image. In some embodiments, the 3D model is a machine learning algorithm, such as a predictive neural network model from 2D to 3D.

[0245] Captured 2D image data store 1216 can be any structure and / or multiple structures suitable for capturing image and / or depth data (e.g., an active database, a relational database, a self-referential database, a table, a matrix, an array, a flat file, a document-oriented storage system, a non-relational No-SQL system, an FTS management system such as Lucene / Solar, and / or the like). Captured 2D image data store 1216 can store images captured by an image capture device of user system 1110. In various embodiments, captured 2D image data store 1216 stores depth data captured by one or more depth sensors of user system 1110. In various embodiments, captured 2D image data store 1216 stores image capture device parameters associated with an image capture device, or capture properties associated with each of a plurality of image captures, or depth captures used to determine a 2D panoramic image. In some embodiments, image data store 1108 stores panoramic 2D images. 2D panoramic images can be determined by 3D and panoramic capture and stitching system 1102 or image stitching and processor system 106. Image capture device parameters may include illumination, color, image capture lens focal length, maximum aperture, tilt angle, etc. Capture properties may include pixel resolution, lens distortion, illumination, and other image metadata.

[0246] 3D panoramic image data store 1218 may be any structure and / or multiple structures suitable for 3D panoramic images (e.g., an active database, a relational database, a self-referential database, a table, a matrix, an array, a flat file, a document-oriented storage system, a non-relational No-SQL system, an FTS management system such as Lucene / Solar, and / or the like). 3D panoramic image data store 1218 may store 3D panoramic images generated by 3D and panoramic capture and stitching system 1102. In various embodiments, 3D panoramic image data store 1218 stores properties associated with an image capture device or properties associated with each of multiple image captures or depth captures used to determine a 3D panoramic image. In some embodiments, 3D panoramic image data store 1218 stores 3D panoramic images. 2D or 3D panoramic images may be determined by 3D and panoramic capture and stitching system 1102 or image stitching and processor system 106.

[0247] Figure 13 A flowchart 1300 is depicted of a 3D panoramic image capture and generation process according to some embodiments. In step 1302, the image capture device can use the image sensor 920 and WFOV lens 918 of Figure 9 to capture multiple 2D images. A wider FOV means that the environment capture system 402 will need fewer scans to obtain a 360° view. The WFOV lens 918 can also be wider horizontally and vertically. In some embodiments, the image sensor 920 captures RGB images. In one embodiment, the image sensor 920 captures black and white images.

[0248] In step 1304, the environment capture system can send the captured 2D images to the image stitching and processing system 1106. The image stitching and processing system 1106 can apply a 3D modeling algorithm to the captured 2D images to generate a panoramic 2D image. In some embodiments, the 3D modeling algorithm is a machine learning algorithm used to stitch the captured 2D images into a panoramic 2D image. In some embodiments, step 1304 may be optional.

[0249] In step 1306, the LiDAR 912 and WFOV lens 918 of Figure 9 can capture LiDAR data. A wider FOV means that the environment capture system 400 will need fewer scans to obtain a 360° view.

[0250] In step 1308, the LiDAR data may be sent to the image stitching and processor system 1106. The image stitching and processor system 1106 may input the LiDAR data and the captured 2D images into a 3D modeling algorithm to generate a 3D panoramic image. The 3D modeling algorithm is a machine learning algorithm.

[0251] In step 1310, the image stitching and processor system 1106 generates a 3D panoramic image. The 3D panoramic image may be stored in the image data storage area 408. In one embodiment, the 3D panoramic image generated by the 3D modeling algorithm is stored in the image stitching and processor system 1106. In some embodiments, as the environment capture system is used to capture various portions of the physical environment, the 3D modeling algorithm may generate a visual representation of a floor plan of the physical environment.

[0252] In step 1312, the image stitching and processor system 1106 may provide at least a portion of the generated 3D panoramic image to the user system 1110. The image stitching and processor system 1106 may provide a visual representation of a floor plan of the physical environment.

[0253] The order of one or more steps of flowchart 1300 can be changed without affecting the final result of the 3D panoramic image. For example, the environment capture system can interleave image capture using the image capture device with LiDAR data or depth information capture using LiDAR 912. For example, the image capture device can capture an image of a section of the physical environment using the image capture device, and then LiDAR 912 can obtain depth information from the section 1605. Once LiDAR 912 obtains depth information from the section, the image capture device can continue to move to capture an image of another section, and then LiDAR 912 can obtain depth information from the section, thereby interleaving the image capture and depth information capture.

[0254] In some embodiments, the devices and / or systems discussed herein employ a single image capture device to capture a 2D input image. In some embodiments, the one or more image capture devices 1116 may represent a single image capture device (or image capture lens). According to some of these embodiments, a user of a mobile device housing an image capture device may be configured to rotate about an axis to generate images at different capture orientations relative to the environment, wherein the common field of view of the images spans up to 360° horizontally.

[0255] In various embodiments, the devices and / or systems discussed herein may employ two or more image capture devices to capture 2D input images. In some embodiments, the two or more image capture devices may be arranged on or within the same mobile housing in positions relative to each other such that their collective field of view spans up to 360°. In some embodiments, paired image capture devices capable of generating stereoscopic image pairs (e.g., with slightly offset but partially overlapping fields of view) may be used. For example, user system 1110 (e.g., a device comprising one or more image capture devices for capturing 2D input images) may include two image capture devices with horizontally offset fields of view capable of capturing stereoscopic image pairs. In another example, user system 1110 may include two image capture devices with vertically offset fields of view capable of capturing vertical stereoscopic image pairs. According to any of these examples, each camera may have a field of view that spans up to 360°. In this regard, in one embodiment, user system 1110 may employ two panoramic cameras with vertical stereo offsets that are capable of capturing paired panoramic images forming a stereoscopic pair (with vertical stereo offsets).

[0256] Positioning component 1118 may include any hardware and / or software configured to capture user system position data and / or user system orientation data. For example, positioning component 1118 may include an IMU to generate user system 1110 position data associated with the one or more image capture devices of user system 1110 used to capture the plurality of 2D images. Positioning component 1118 may include a GPS unit to provide GPS coordinate information associated with the plurality of 2D images captured by the one or more image capture devices. In some embodiments, positioning component 1118 may associate the user system position data and orientation data with corresponding images captured using the one or more image capture devices of user system 1110.

[0257] Various embodiments of the device provide users with 3D panoramic images of indoor and outdoor environments. In some embodiments, the device can effectively and quickly provide users with 3D panoramic images of indoor and outdoor environments using a single wide field of view (FOV) lens and a single light and detection and ranging sensor (LiDAR sensor).

[0258] The following is an example use case for the example device described herein. The following use case is one of the embodiments. Different embodiments of the device as discussed herein may include one or more features and capabilities similar to those in this use case.

[0259] Figure 14 Depicted is a flow diagram of a 3D and panoramic capture and stitching process 1400 in accordance with some embodiments. Figure 14The flowchart of FIG. 11 refers to the 3D and panoramic capture and stitching system 1102 as including an image capture device, but in some embodiments, the data capture device may be a user system 1110 .

[0260] In step 1402, the 3D and panoramic capture and stitching system 1102 may receive a plurality of 2D images from at least one image capture device. The image capture device of the 3D and panoramic capture and stitching system 1102 may be or include a complementary metal oxide semiconductor (CMOS) image sensor. In various embodiments, the image capture device is a charge coupled device (CCD). In one example, the image capture device is a red-green-blue (RGB) sensor. In one embodiment, the image capture device is an IR sensor. Each of the plurality of 2D images may have a field of view that partially overlaps with at least one other image in the plurality of 2D images. In some embodiments, at least some of the plurality of 2D images are combined to produce a 360° view of a physical environment (e.g., indoors, outdoors, or both).

[0261] In some embodiments, all of the multiple 2D images are received from the same image capture device. In various embodiments, at least a portion of the multiple 2D images are received from two or more image capture devices of the 3D and panoramic capture and stitching system 1102. In one example, the multiple 2D images include a set of RGB images and a set of IR images, where the IR images provide depth data to the 3D and panoramic capture and stitching system 1102. In some embodiments, each 2D image can be associated with depth data provided by a LiDAR device. In some embodiments, each 2D image can be associated with positioning data.

[0262] In step 1404, the 3D and panoramic capture and stitching system 1102 may receive capture parameters and image capture device parameters associated with each of the received plurality of 2D images. The image capture device parameters may include illumination, color, image capture lens focal length, maximum aperture, field of view, etc. Capture properties may include pixel resolution, lens distortion, illumination, and other image metadata. The 3D and panoramic capture and stitching system 1102 may also receive positioning data and depth data.

[0263] In step 1406, the 3D and panoramic capture and stitching system 1102 may obtain the information received from steps 1402 and 1404 for stitching the 2D images to form a 2D panoramic image. Figure 15 The process of stitching 2D images is further discussed in the flowchart.

[0264] In step 1408, the 3D and panoramic capture and stitching system 1102 can apply the 3D machine learning model to generate a 3D representation. The 3D representation can be stored in the 3D panoramic image data storage area. In various embodiments, the 3D representation is generated by the image stitching and processor system 1106. In some embodiments, as the environment capture system is used to capture various portions of the physical environment, the 3D machine learning model can generate a visual representation of the floor plan of the physical environment.

[0265] In step 1410, the 3D and panoramic capture and stitching system 1102 may provide at least a portion of the generated 3D representation or model to the user system 1110. The user system 1110 may provide a visual representation of a floor plan of the physical environment.

[0266] In some embodiments, the user system 1110 may send the plurality of 2D images, capture parameters, and image capture parameters to the image stitching and processor system 1106. In various embodiments, the 3D and panoramic capture and stitching system 1102 may send the plurality of 2D images, capture parameters, and image capture parameters to the image stitching and processor system 1106.

[0267] Image stitching and processing system 1106 can process multiple 2D images captured by the image capture device of user system 1110 and stitch them into a 2D panoramic image. The 2D panoramic image processed by image stitching and processing system 1106 can have a higher pixel resolution than the 2D panoramic image obtained by 3D and panoramic capture and stitching system 1102.

[0268] In some embodiments, the image stitching and processing system 106 can receive the 3D representation and output a 3D panoramic image having a higher pixel resolution than the pixel resolution of the received 3D panoramic image. The higher pixel resolution panoramic image can be provided to an output device, such as a computer screen, a projector screen, etc., having a higher screen resolution than the user system 1110. In some embodiments, the higher pixel resolution panoramic image can provide the output device with more detail and can be magnified.

[0269] Figure 15 Depicted showing Figure 1415. A flowchart of a step in a 3D and panoramic capture and stitching process for capturing and stitching a 3D image and a panoramic image is provided. In step 1502, the image capture position module 1204 may determine image capture device position data associated with each image captured by the image capture device. The image capture position module 1204 may utilize the IMU of the user system 1110 to determine the position data of the image capture device (or the field of view of the lens of the image capture device). The position data may include the orientation, angle, or tilt of the one or more image capture devices when capturing the one or more 2D images. One or more of the cropping module 1208, the graphic cutting module 1210, or the blending module 1212 may utilize the orientation, angle, or tilt associated with each of the multiple 2D images to determine how to warp, cut, and / or blend the images.

[0270] In step 1504, the cropping module 1208 may warp one or more of the plurality of 2D images so that two images can be aligned together to form a panoramic image while preserving certain characteristics of the image, such as keeping straight lines straight. The output of the cropping module 1208 may include the number of pixel columns and rows to offset each pixel of the image to straighten the image. The offset amount for each image may be output in the form of a matrix indicating the number of pixel columns and rows to offset each pixel of the image. In this embodiment, the cropping module 1208 may determine the amount of warping required for each of the plurality of 2D images based on an estimate of the image capture pose of each of the plurality of 2D images.

[0271] In step 1506, the graph cut module 1210 determines where to cut or slice one or more of the plurality of 2D images. In this embodiment, the graph cut module 1210 may determine where to cut or slice each of the plurality of 2D images based on an image capture pose estimate and an image warp for each of the plurality of 2D images.

[0272] In step 1508, the stitching module 1206 can stitch the two or more images together using the edges of the images and / or cutouts of the images. The stitching module 1206 can align and / or position the images based on objects detected within the images, distortions of the images, cutouts, etc.

[0273] In step 1510, the blending module 1212 can adjust the color at the seam (e.g., the stitching of two images) or the location where one image touches or connects to another image. The blending module 1212 can determine the desired amount of color blending based on one or more image capture positions from the image capture position module 1204, the image warp from the cropping module 1208, and the graphic cut from the graphic cut module 1210.

[0274] The order of one or more steps of the 3D and panoramic capture and stitching process 1400 may be changed without affecting the final result of the 3D panoramic image. For example, the environment capture system may interleave image capture using an image capture device with LiDAR data or depth information capture. For example, an image capture device may capture a portion of the physical environment using an image capture device. Figure 16 1605, and the LiDAR 612 then obtains depth information from segment 1605. Once the LiDAR obtains depth information from segment 1605, the image capture device may continue to move to capture an image of another segment 1610, and the LiDAR 612 then obtains depth information from segment 1610, thereby interleaving image capture and depth information capture.

[0275] Figure 16 A block diagram of an example digital device 1602 is depicted in accordance with some embodiments. Any of the user system 1110, the 3D panoramic capture and stitching system 1102, and the image stitching and processor system may include an instance of the digital device 1602. The digital device 1602 includes a processor 1604, a memory 1606, a storage device 1608, an input device 1610, a communication network interface 1612, an output device 1614, an image capture device 1616, and a positioning component 1618. The processor 1604 is configured to execute executable instructions (e.g., a program). In some embodiments, the processor 1604 includes a circuit or any processor capable of processing executable instructions.

[0276] Memory 1606 stores data. Some examples of memory 1606 include storage devices such as RAM, ROM, RAM cache, virtual memory, etc. In various embodiments, working data is stored in memory 1606. Data in memory 1606 can be cleared or eventually transferred to storage device 1608.

[0277] Storage device 1608 includes any storage device configured to retrieve and store data. Some examples of storage device 1608 include a flash drive, a hard drive, an optical drive, and / or magnetic tape. Each of memory 1606 and storage device 1608 includes a computer-readable medium that stores instructions or programs executable by processor 1604.

[0278] Input device 1610 is any device for inputting data (e.g., a touch keyboard, a stylus). Output device 1614 outputs data (e.g., a speaker, a display, a virtual reality headset). It should be understood that storage device 1608, input device 1610, and output device 1614 are optional. In some embodiments, output device 1614 is optional. For example, a router / switch may include processor 1604 and memory 1606, as well as devices for receiving and outputting data (e.g., a communication network interface 1612 and / or output device 1614).

[0279] The communication network interface 1612 can be coupled to a network (e.g., the communication network 104) via the communication network interface 1612. The communication network interface 1612 can support communication via an Ethernet connection, a serial connection, a parallel connection, and / or an ATA connection. The communication network interface 1612 can also support wireless communications (e.g., 802.16a / b / g / n, WiMAX, LTE, Wi-Fi). It will be apparent that the communication network interface 1612 can support many wired and wireless standards.

[0280] Components can be hardware or software. In some embodiments, components can configure one or more processors to perform functions associated with the components. Although different components are discussed herein, it should be understood that the server system can include any number of components that perform any or all of the functions discussed herein.

[0281] The digital device 1602 may include one or more image capture devices 1616. The one or more image capture devices 1616 may include, for example, an RGB camera, an HDR camera, a video camera, etc. According to some embodiments, the one or more image capture devices 1616 may also include a video camera capable of capturing video. In some embodiments, the one or more image capture devices 1616 may include an image capture device that provides a relatively standard field of view (e.g., approximately 75°). In other embodiments, the one or more image capture devices 1616 may include a camera that provides a relatively wide field of view (e.g., from approximately 120° up to 360°), such as a fisheye camera, etc. (e.g., the digital device 1602 may include or be included in the environment capture system 400).

[0282] Components can be hardware or software. In some embodiments, components can configure one or more processors to perform functions associated with the components. Although different components are discussed herein, it should be understood that the server system can include any number of components that perform any or all of the functions discussed herein.

Claims

1. An image capturing device, comprising: a housing having a front side and a rear side; a first motor within the housing at a first position between the front side and the rear side of the housing, the first motor configured to rotate the image capture device at least 360 degrees about a first axis; a wide angle lens within the housing of the image capture device at a second position along the first axis between the front side and the rear side of the housing, the second position being substantially at a point of no parallax, the wide angle lens having a field of view away from the front side extending the housing; an image sensor within the housing of the image capture device and configured to generate an image signal from light received by the wide angle lens; a LiDAR in a third position within the housing of the image capture device, the LiDAR configured to generate laser pulses and generate a depth signal; a second motor within the housing of the image capture device; as well as A mirror coupled to the second motor, the second motor configured to rotate the mirror about a second axis, the mirror comprising an angled surface configured to receive the laser pulses from the LiDAR and direct the laser pulses about the second axis. 2 . The image capture device of claim 1 , wherein the image sensor is configured to generate a first plurality of images when the image capture device is stationary and pointed in a first direction. 3 . The image capture device of claim 2 , wherein the first motor is configured to rotate the image capture device about the first axis after generating the first plurality of images.

4. The image capture device of claim 3, wherein the image sensor does not generate an image while the first motor causes the image capture device to rotate, and wherein the LiDAR generates a depth signal based on the laser pulses while the first motor causes the image capture device to rotate.

5. The image capture device of claim 3, wherein the image sensor is configured to generate a second plurality of images when the image capture device is stationary and pointing in a second direction, and the first motor is configured to rotate the image capture device 90 degrees about the first axis after generating the second plurality of images.

6. An image capture device according to claim 5, wherein the image sensor is configured to generate a third plurality of images when the image capture device is stationary and pointing in a third direction, and the first motor is configured to rotate the image capture device 90 degrees around the first axis after generating the third plurality of images.

7. An image capture device according to claim 6, wherein the image sensor is configured to generate a fourth plurality of images when the image capture device is stationary and pointing in a fourth direction, and the first motor is configured to rotate the image capture device 90 degrees around the first axis after generating the fourth plurality of images.

8. The image capture device of claim 7, further comprising a processor configured to blend frames of the first plurality of images before the image sensor generates the second plurality of images.

9. The image capture device of claim 7, further comprising a remote digital device in communication with the image capture device and configured to generate a 3D visualization based on the first, second, third, and fourth plurality of images and the depth signal, the remote digital device being configured to generate the 3D visualization by using no more than the first, second, third, and fourth plurality of images.

10. The image capture device of claim 9, wherein the first plurality of images, the second plurality of images, the third plurality of images, and the fourth plurality of images are generated between rotations that combine to rotate the image capture device 270 degrees about the first axis.

11. The image capture device of claim 4, wherein a speed or rotation of the mirror about the second axis increases when the first motor turns the image capture device.

12. The image capture device of claim 1, wherein the angled surface of the reflector is at least 45 degrees from the second axis.

13. The image capture device of claim 1, wherein the LiDAR emits the laser pulses in a direction opposite the front side of the housing of the image capture device.

14. A method comprising: receiving light from a wide angle lens of a device, the wide angle lens being within a housing of the device, the light being received from a field of view of the wide angle lens, the field of view extending away from a front side of the housing; generating a first plurality of images using the light from the wide angle lens by an image sensor of the device, the image sensor being within the housing of the device; Rotating the device at least 360 degrees about a first axis by a first motor, the first motor being in a first position within the housing between the front side and the rear side of the housing, the wide-angle lens being in a second position along the first axis, the second position being substantially at a point of no parallax; rotating the reflector having the angled surface about a second axis by a second motor within the housing of the device; generating laser pulses by a LiDAR at a third position within the housing of the device, the laser pulses being directed to the rotating mirror while the device rotates about the first axis; as well as A depth signal is generated by the LiDAR based on the laser pulses.

15. The method of claim 14, wherein generating the first plurality of images by the image sensor occurs before rotating the device about the first axis.

16. The method of claim 15, wherein the image sensor does not generate an image while the first motor rotates the device, and wherein the LiDAR generates the depth signal based on the laser pulses while the first motor rotates the device.

17. The method according to claim 16, further comprising: generating a second plurality of images by the image sensor when the device is stationary and pointed in a second direction; and After generating the second plurality of images, the device is rotated 90 degrees about the vertical axis by the first motor.

18. The method according to claim 17, further comprising: generating a third plurality of images by the image sensor when the device is stationary and pointed in a third direction; and After generating the third plurality of images, the device is rotated 90 degrees about the first axis by the first motor.

19. The method according to claim 18, further comprising: A fourth plurality of images is generated by the image sensor when the device is stationary and pointed in a fourth direction.

20. The method of claim 19, further comprising generating a 3D visualization using the first, second, third, and fourth pluralities of images and based on the depth signal, the generating the 3D visualization not using any other images.

21. The method of claim 17, further comprising blending frames of the first plurality of images before the image sensor generates the second plurality of images.

22. The method of claim 19, wherein the first plurality of images, the second plurality of images, the third plurality of images, and the fourth plurality of images are generated between rotations that combine to rotate the device at least 360 degrees about the second axis.

23. The method of claim 14, wherein a speed or rotation of the mirror about the second axis increases as the first motor rotates the device.

Images