Capturing image of spherical site

Abstract

The invention relates to capturing an image of a spherical site. An image processing server for transforming an image to project onto a media plane of a venue, the image processor comprising: a memory configured to store instructions; and a processor configured to execute instructions that, when executed by the processor, configure the processor to project three-dimensional coordinates of a plurality of pixels of a media plane onto two-dimensional coordinates of an image space of an image to provide a plurality of two-dimensional points projected onto the image, the color information of the plurality of pixels of the image is interpolated based on the color information of the plurality of pixels of the media plane, and the color information of the plurality of pixels is provided to the field so that the image is projected onto the media plane.

Description

[0001] This application is a divisional application of the application patent application with the application number 202380081950.9, the filing date of 30 November 2023, and the invention title of “Capturing images of a spherical venue”.

[0002] Cross Reference to Related Applications

[0003] This application claims priority to U.S. Patent Application No. 18 / 332,855 filed on June 12, 2023, and U.S. Patent Application No. 18 / 332,874 filed on June 12, 2023, both of which claim the benefit of U.S. Provisional Patent Application No. 63 / 434,309 filed on December 21, 2022, which are incorporated by reference herein in their entirety. BACKGROUND

[0004] Content creators often use conventional ultra-wide angle lenses, such as, for example, conventional fisheye lenses, to capture conventional images to be displayed by a conventional three-dimensional media plane. Conventional fisheye lenses represent a class of ultra-wide angle lenses that produce strong visual distortions, such as, for example, a convex, non-linear appearance, that are intended to create one or more hemispherical images for display by a conventional three-dimensional media plane. A conventional primary viewing segment can often be associated with a conventional fisheye lens at a top or crown of a conventional three-dimensional media plane. Typically, the conventional primary viewing segment can be characterized as having the highest optical image quality, such as, for example, resolution, as compared to other viewing segments of the conventional three-dimensional media plane. The optical image quality of one or more images captured by a conventional fisheye lens and presented onto a conventional three-dimensional media plane gradually decreases from the conventional primary viewing segment toward a bottom or pop-up of the conventional three-dimensional media plane, with the lowest optical image quality at the bottom of the conventional three-dimensional media plane.

[0005] Content creators often capture conventional images to be displayed by a conventional three-dimensional media plane during an event. Typically, an event can be characterized as including one or more performers positioned toward a bottom of a conventional three-dimensional media plane. The conventional three-dimensional media plane can often display images while the one or more performers are performing. As a result, an audience experiencing the event within the conventional venue will generally focus their field of view on the one or more performers toward the bottom of the conventional three-dimensional media plane. As a result, the audience will view images on the conventional three-dimensional media plane at their lowest optical image quality. The audience is required to shift their field of view toward the conventional primary viewing segment at the top of the conventional three-dimensional media plane (i.e., look up) to experience images at the highest optical image quality, but this causes the one or more performers to no longer be within their field of view. BRIEF DESCRIPTION OF DRAWINGS

[0006] The present disclosure is described with reference to the accompanying drawings. In the drawings, like reference numerals indicate like or functionally similar elements. Additionally, the left-most digit(s) of the reference numerals identifies the drawings in which the reference numeral first appears. In the drawings:

[0007] FIG. 1A and FIG. 1B illustrates a graphical representation of an example place, in accordance with some example embodiments of the present disclosure;

[0008] FIG. 2A illustrates a simplified block diagram of an example image capture system, in accordance with some example embodiments of the present disclosure;

[0009] FIG. 2B illustrates a flowchart of example operations of an example camera system that can be implemented within an example image capture system, in accordance with some example embodiments of the present disclosure;

[0010] FIG. 3A and FIG. 3B illustrates a simplified block diagram of an example camera lens system that can be implemented within an example camera system, in accordance with some example embodiments of the present disclosure;

[0011] FIG. 4A and FIG. 4B illustrates a simplified block diagram of an example camera lens housing that can be implemented within an example camera system, in accordance with some example embodiments of the present disclosure;

[0012] FIG. 5A and FIG. 5B illustrates a simplified block diagram of an example camera system, in accordance with some example embodiments of the present disclosure;

[0013] FIG. 6 illustrates a simplified block diagram of an example image projection system, in accordance with some example embodiments of the present disclosure;

[0014] FIG. 7 illustrates a flowchart of an example kernel-based sampling technique that can be implemented within an example projection system, in accordance with some example embodiments of the present disclosure;

[0015] FIG. 8 and FIG. 9 illustrates an example kernel-based sampling technique that can be implemented within an example projection system, in accordance with some example embodiments of the present disclosure;

[0016] FIG. 10 illustrates a simplified block diagram of an example computer system that can be implemented within an example image capture system and / or an example image projection system, in accordance with some example embodiments of the present disclosure.

[0017] The present disclosure will now be described with reference to the accompanying drawings. DETAILED DESCRIPTION

[0018] The following disclosure provides many different embodiments, or examples, for implementing different features of the provided subject matter. Specific examples of components and arrangements are described below to explain the present disclosure. These are, of course, merely examples and are not intended to limit the scope of the disclosure. One skilled in the art will recognize that the various aspects of the present disclosure can be practiced without one or more of the specific details set forth herein. In other instances, well-known structures and functions have not been described in detail in order to avoid obscuring the concepts of the present disclosure. The detailed description below is further to be regarded as merely illustrative in nature and is not treated as limiting on the scope of the disclosure. The present disclosure is susceptible to numerous modifications and alternative methods of

[0019] SUMMARY

[0020] The systems, methods, and devices disclosed herein can include an exemplary image capture system to capture light related to one or more images within its field of view; and / or an exemplary image projection system to transform one or more images for projection onto a three-dimensional media plane of a three-dimensional venue. The exemplary image capture system can direct light rays captured by the exemplary image capture system onto an image sensor associated with the exemplary image capture system. As will be described in further detail below, the exemplary image capture system can focus these light rays toward a periphery or edge of the image sensor. As a result, the three-dimensional venue can display a highest optical image quality of one or more images toward a bottom or pop-up portion of the three-dimensional media plane. Moreover, the exemplary image capture system can be specially manufactured to heterogeneously (e.g., non-uniformly) distribute light rays captured by the exemplary image capture system onto the image sensor to further enhance the highest optical image quality of one or more images. As will be described in further detail below, the exemplary image projection system can project one or more images onto a three-dimensional media plane of a three-dimensional venue. As part of such projection, the exemplary image projection system can mathematically transform two-dimensional coordinates of pixels of one or more images onto three-dimensional coordinates of the three-dimensional media plane to project one or more images onto the three-dimensional media plane. And as part of such projection, the exemplary image projection system can statistically interpolate color information in one or more images to be projected onto the three-dimensional media plane.

[0021] Projecting images onto exemplary venues of the present disclosure

[0022] FIG. 1A And FIG. 1B A graphical representation of an exemplary venue is illustrated in accordance with some example embodiments of the present disclosure. In FIG. 1A And FIG. 1BIn the exemplary embodiments shown in FIGS. 1-3, venue 100 represents a location at which an event is held. For example, without departing from the spirit and scope of the present disclosure, venue 100 can represent a music venue (e.g., a music theater, a music club, and / or a music hall), a sports venue (e.g., an arena, a convention center, and / or a stadium), and / or any other suitable venue, as will be apparent to those of ordinary skill in the art. Without departing from the spirit and scope of the present disclosure, the event can include a music event, a theatrical event, a sports event, a movie, and / or any other suitable event, as will be apparent to those of ordinary skill in the art. In FIG. 1A and FIG. 1B In the exemplary embodiments shown in FIGS. 1-3, venue 100 can represent a three-dimensional structure, such as a hemispherical structure, also referred to as a hemispherical dome, for holding an event. In some embodiments, venue 100 can include a three-dimensional media plane 102 for displaying one or more images that can be associated with the event that is dispersed across an interior or a vault of venue 100. In some embodiments, three-dimensional media plane 102 can include a series of rows and a series of columns of picture elements, also referred to as pixels, in three-dimensional space. In these embodiments, the pixels can be implemented using one or more light-emitting diode (LED) displays, one or more organic light-emitting diode (OLED) displays, and / or one or more quantum dot (QD) displays, for example. For example, three-dimensional media plane 102 can include a three-dimensional media plane of approximately 16000 x 16000 resolution in three-dimensional space that encircles an interior of venue 100 to form a visual display of approximately 160,000 square feet.

[0023] In some embodiments, venue 100 can project one or more images onto three-dimensional media plane 102. In these embodiments, one or more images can be projected onto three-dimensional media plane 102 during the event to enhance the visual experience of the audience watching the event. As FIG. 1AAs shown in FIG. 1, the three-dimensional media plane 102 can include a viewer primary viewing segment 104 positioned along an interior or a vault of the three-dimensional media plane 102 having a highest optical image quality. In some embodiments, the viewer primary viewing segment 104 can be located approximately at a waist of the three-dimensional media plane 102, which is approximately located at a middle position between a top and a base, where an approximate center of the viewer primary viewing segment 104 is represented in a spherical coordinate system as (R, A, Q). The viewer primary viewing segment 104 can be characterized as having a highest optical image quality (e.g., resolution) compared to other viewing segments of the three-dimensional media plane 102. In some embodiments, an optical image quality of one or more images projected onto the three-dimensional media plane 102 decreases from the highest optical image quality of the viewer primary viewing segment 104 along the interior of the three-dimensional media plane 102 towards another viewing segment diametrically opposite the viewer primary viewing segment 104. As will be described in further detail below, an exemplary image capture system can be used to capture one or more images having a highest optical image quality located within the viewer primary viewing segment 104 when projected onto the three-dimensional media plane 102. Also, as will be described in further detail below, an exemplary image projection system can be used to transform two-dimensional coordinates of the one or more images onto three-dimensional coordinates of the three-dimensional media plane to allow the one or more images to be projected onto the three-dimensional media plane.

[0024] In some embodiments, a center of the conventional primary viewing segment 112 as described above can be represented in a spherical coordinate system as (r, a, q). In these embodiments, a distance D R between the center of the viewer primary viewing segment 104 and the center of the conventional primary viewing segment 112 can be represented as:

[0025]

[0026] and a difference D θ in polar angle between the viewer primary viewing segment 104 and the center of the conventional primary viewing segment can be represented as:

[0027] D θ = Q - q (2)

[0028] In some embodiments, the center of the conventional primary viewing segment 112 can be considered to be offset from the center of the viewer primary viewing segment 104 by a difference D θ . For example, the difference D θ may be between approximately 30 degrees and approximately 90 degrees. In this example, the viewer primary viewing segment 104 can be considered to be offset from the conventional primary viewing segment 112 by between approximately 30 degrees and approximately 90 degrees.

[0029] As FIG. 1BAs shown in , venue 100 may include one or more seating sections where audience members may be seated to experience an event. In some embodiments, a primary viewing section 104 for the audience may be specifically designated by, for example, an image capture system 200, described in further detail below, to allow one or more audience members 106 among the seated audience members within venue 100 to view one or more images projected onto three-dimensional media plane 102 at their highest optical image quality. In some embodiments, for example, one or more audience members 106 may include audience members from one or more rows of seats within venue 100 and / or one or more seating sections within venue 100. And as FIG. 1B As shown in , the audience primary viewing section 104 can be specifically customized to coincide with the field of view 108 of one or more audience members 106 as they experience the event. By way of example, field of view 108 can correspond to the field of view of audience members within a primary seating area (e.g., a luxury box) within venue 100. In some embodiments, it can be considered that one or more audience members 106 experience the one or more images projected at their highest optical image quality. In some embodiments, as described above, the event can be characterized as having one or more performers positioned toward the bottom of three-dimensional media plane 102. In these embodiments, the one or more performers can be located on a stage 110 positioned toward the bottom of three-dimensional media plane 102. In these embodiments, the audience primary viewing section 104 can be located behind the one or more performers to allow one or more audience members 106 to simultaneously view the one or more performers and the one or more images at their highest optical image quality. In other words, the audience primary viewing section 104 can be located within the field of view 108 of one or more audience members 106 while the one or more audience members 106 are viewing the one or more performers.

[0030] Exemplary image capture system for capturing images

[0031] FIG. 2A A simplified block diagram of an exemplary image capture system according to some exemplary embodiments of the present disclosure is illustrated. FIG. 2A In the exemplary embodiment shown in FIG, the image capture system 200 captures a three-dimensional media plane that can be projected onto a venue (such as the one described above). FIG. 1A and FIG. 1B As will be described in further detail below, the image capture system 200 can be used to capture a viewer's primary viewing area located in the three-dimensional media plane (such as the one described above). FIG. 1A and FIG. 1BAs will be described in further detail below, the image capture system 200 can direct the light captured by the image capture system 200 onto an image sensor associated with the image capture system 200. As will be described in further detail below, the image capture system 200 can focus these light rays toward the periphery or edge of the image sensor. As a result, the three-dimensional venue can display the highest optical image quality for one or more images with the highest optical image quality that are located within the main viewing section of the audience of the three-dimensional media. Moreover, the image capture system 200 can be specially manufactured to distribute the light captured by the exemplary image capture system heterogeneously (e.g., non-uniformly) onto the image sensor to further enhance the highest optical image quality of one or more images. As FIG. 2A As shown in , image capture system 200 may include camera system 202 having camera lens system 204 and camera assembly 206, which may be communicatively coupled to image recording system 208 via communication network 210. FIG. 2A 202 as including multiple separate devices, but those skilled in the relevant art will recognize that one or more of these devices may be combined without departing from the spirit and scope of the present disclosure. For example, the camera system 202 may include the camera lens system 204, the camera assembly 206, and / or the image recording system 208 as a single separate device without the communication network 210, as will be apparent to those skilled in the relevant art without departing from the spirit and scope of the present disclosure.

[0032] exist FIG. 2A In the exemplary embodiment shown in , the camera lens system 204 projects light associated with one or more images (e.g., a scene) within its field of view onto an image sensor 212 of a camera assembly 206, which will be described in further detail below. In some embodiments, the camera lens system 204 can focus (e.g., converge) the light captured on the image sensor 212 to generate one or more images for projection onto a three-dimensional media plane of the venue. For example, the camera lens system 204 can focus light reflected from one or more physical objects within the scene onto the image sensor 212 to generate one or more images of the one or more physical objects for projection onto the three-dimensional media plane of the venue. FIG. 2A In the exemplary embodiment shown in , the camera lens system 204 may include a camera lens housing and a camera lens system. In some embodiments, for example, the camera lens housing may be implemented to form a viewing angle control lens, such as a shift lens or a tilt-shift lens. FIG. 1A and FIG. 1BIn some embodiments, the image capture system 200 can utilize a perspective control lens to focus (e.g., converge) light captured by the image capture system 200 onto one or more segments of the image sensor 212 associated with the audience primary viewing segment of the three-dimensional media plane. In some embodiments, the perspective control lens can change an orientation or position of the camera lens system relative to the camera assembly 206, e.g., tilt, shift, and / or rotate, to designate the one or more segments of the image sensor 212. For example, the perspective control lens can turn an orientation or position of a center of the camera lens system, e.g., a center of a super wide-angle lens such as a fisheye lens or rectilinear lens, relative to the image sensor 212. In general, a super wide-angle lens represents any suitable lens having a field of view between about one hundred (100) degrees and about one hundred eighty (180) degrees, as will be recognized by one of ordinary skill in the relevant art without departing from the spirit and scope of the present disclosure. In this example, the perspective control lens can turn the orientation or position of the center of the camera lens system toward a periphery, e.g., an edge, of the image sensor 212 to focus light captured by the center of the camera lens system toward the periphery of the image sensor 212. In some embodiments, the periphery, e.g., the edge, of the image sensor 212 can be approximated as an outermost one-eighth to one-quarter of a surface area of the image sensor 212. Accordingly, when one or more images projected near the periphery of the image sensor 212 are projected onto the three-dimensional media plane, as described in FIG. 1A and FIG. 1B the highest optical image quality of the one or more images can be positioned along an interior of the three-dimensional media plane within the audience primary viewing segment.

[0033] In some embodiments, the camera lens system may include a simple single lens of transparent material; however, as will be apparent to those skilled in the relevant art, more complex composite lenses of transparent materials (such as doublets, triplets, and / or achromatic lenses) are also possible without departing from the spirit and scope of the present disclosure. In these embodiments, the transparent material may include glass, crystal, and / or plastic (such as acrylic). In some embodiments, these complex composite lenses may be configured and arranged to form an ultra-wide-angle lens, such as a fisheye lens that produces strong visual distortion intended to create one or more hemispherical images, and / or a rectilinear lens that produces one or more images in which straight features (such as the edges of building walls) appear straight rather than curved as in a fisheye lens with little or no barrel or pincushion distortion. In some embodiments, the ultra-wide-angle lens may be specifically manufactured to direct the light captured by the camera lens system so that it is heterogeneously (e.g., non-uniformly) distributed about the approximate center of the image sensor 212. In these embodiments, the angular distribution of light may be characterized as non-uniform across the image sensor 212, compared to the conventional ultra-wide-angle lens described above, which projects light uniformly. For example, the camera lens system can focus light onto the image sensor 212 so that it is more concentrated near the center of the image sensor 212 than at the periphery of the image sensor 212. In some embodiments, the camera lens system can concentrate light near the center of the image sensor 212 to project more detail in one or more images, for example, to project more detail of a scene near the center of the image sensor 212. Thus, when the camera lens system 204 includes a perspective control lens that heterogeneously distributes light captured by the perspective control lens, the one or more images projected into the viewer's primary viewing area include even more detail, and thus, even higher resolution, than when the camera lens system 204 uses only a perspective control lens.

[0034] The camera assembly 206 captures light focused by the camera lens system 204 onto the image sensor 212 to provide one or more digital image signals associated with the one or more images, also referred to as raw image data. In some embodiments, the camera assembly 206 can reconstruct one or more images from the one or more digital image signals. FIG. 2AIn the exemplary embodiment shown in FIG. 2, camera assembly 206 can include image sensor 212 and processor 214. Generally, image sensor 212 converts light (i.e., photons) focused onto image sensor 212 by camera lens system 204 into an electrical signal. In some embodiments, image sensor 212 can convert the electrical signal from a representation in an analog signal domain to a representation in a digital signal domain to provide one or more digital image signals stored by image recording system 208 as described in further detail below. In some embodiments, image sensor 212 can include small picture elements (also referred to as pixels), which can include a light-sensitive element, a microlens, and / or a microelectronic component. In some embodiments, the pixels can be configured and arranged in a series of rows and a series of columns to form an array of pixels, such as a square array of pixels. In these embodiments, image sensor 212 can include 18,000 rows of pixels and 18,000 columns of pixels to form a 18,000 x 18,000 square array of pixels. In some embodiments, image sensor 212 can be implemented as a charge-coupled device (CCD) or an active pixel sensor that can be fabricated with complementary metal-oxide-semiconductor (CMOS) and / or n-type metal-oxide-silicon (NMOS) technology. In these embodiments, image sensor 212 can be implemented as a color sensor that includes a color mask, such as a Bayer mask for example, that absorbs undesired color wavelengths such that each pixel of image sensor 212 is sensitive to a particular color wavelength; and / or can be implemented as a monochrome sensor that does not include a color mask such that each pixel of image sensor 212 is sensitive to all visible light wavelengths. In these embodiments, for example, the one or more digital image signals can include color information for each pixel of image sensor 212, such as luminance and / or chrominance components of a YUV color model, and / or red, green, and / or blue components of an RGB color model.

[0035] The processor 214 can provide one or more digital image signals produced by the image sensor 212 to the image recording system 208. Alternatively or additionally, the processor 214 can reconstruct one or more images from the one or more digital image signals and then provide the one or more images to the image recording system 208. In these embodiments, the processor 214 can implement one or more digital image processing techniques, also referred to as digital picture processing techniques, to process the one or more digital image signals produced by the image sensor 212 in order to reconstruct the one or more images from the one or more digital image signals. In some embodiments, the one or more digital image processing techniques can include decoding, demosaicing, defective pixel removal, white balancing, noise reduction, color conversion, tone reproduction, compression, removal of system noise, dark frame subtraction, optical correction, contrast manipulation, de-sharpening masking, and / or any other suitable well-known digital image processing techniques, as would be apparent to one of ordinary skill in the relevant art, without departing from the spirit and scope of the present disclosure. In some embodiments, the processor 214 can format the one or more digital image signals and / or the one or more images for transmission to the image recording system 208 over the communication network 210. In some embodiments, the processor 214 can compress the one or more digital image signals and / or the one or more images using, for example, lossless compression techniques, such as Lempel-Ziv based lossless compression techniques, and / or lossy compression techniques, such as discrete cosine transform (DCT) based lossy compression techniques. In some embodiments, the processor 214 can include or be coupled to an electro-optical converter to transform the one or more digital image signals from electrical signals to optical signals for transmission over an optical fiber network.

[0036] The image recording system 208 can store the one or more digital image signals and / or the one or more images provided by the processor 214. As will be described in further detail below, the one or more digital image signals and / or the one or more images can be further processed by the image projection system for projection onto the screen 202 in a manner similar to that described above in connection with the image recording system 204. FIG. 1A and FIG. 1BThe three-dimensional media plane is projected onto the venue plane in a substantially similar manner as described above with respect to the three-dimensional media plane. In some embodiments, the image recording system 208 can store the one or more digital image signals as raw camera image files having radiometric characteristics of the light captured by the image capture system. For example, these radiometric characteristics can include color information for each pixel of the image sensor, such as luminance and / or chrominance components of a YUV color model, and / or red, green, and / or blue components of an RGB color model. Alternatively or additionally, without departing from the spirit and scope of the present disclosure, the image recording system 208 can store the one or more images in any suitable well-known image file format, such as, for example, a Joint Photographic Experts Group (JPEG) image file format, an Exchangeable image file format (EXIF), a Tagged Image File Format (TIFF), a Graphics Interchange Format (GIF), a Bitmap Image File (BMP) format, or a Portable Network Graphics (PNG) image file format, as will be apparent to those of ordinary skill in the relevant art. In some embodiments, the image recording system 208 can include a machine-readable medium to store the one or more digital image signals and / or the one or more images in a form readable by a machine, such as a computing device. In these embodiments, the machine-readable medium can include read-only memory (ROM), random access memory (RAM), magnetic disk storage media, optical storage media, flash memory devices, and the like. Alternatively or additionally, the machine-readable medium can include a hard disk drive (e.g., a solid state drive), a floppy disk drive and associated removable disk, a CD-ROM drive, an optical drive, a flash memory or removable memory cartridge, to durably store the one or more digital image signals of the camera assembly 206.

[0037] The communication network 210 communicatively couples the camera system 202 and the image recording system 208. Without departing from the spirit and scope of the present disclosure, the communication network 210 can be implemented as a wireless communication network, a wired communication network, and / or any combination thereof, as will be apparent to those of ordinary skill in the relevant art. In some embodiments, the communication network 210 can include a fiber optic network and / or a coaxial network that uses fiber optic and / or coaxial cables to deliver the one or more digital image signals and / or the one or more images from the camera system 202 to the image recording system 208. In some embodiments, the communication network 210 can include a hybrid fiber coaxial cable (HFC) network that combines fiber optic and coaxial cables to deliver the one or more digital image signals and / or the one or more images from the camera system 202 to the image recording system 208.

[0038] Exemplary camera system that can be implemented within an exemplary camera system

[0039] FIG. 2BA flow diagram illustrating example operations of an example camera system that can be implemented in an example image capture system, in accordance with some example embodiments of the present disclosure, is shown. The present disclosure is not limited to this operational description. Rather, one of ordinary skill in the relevant art will appreciate that other operational control flows are within the scope and spirit of the present disclosure. The following discussion describes an example operational control flow 250 for projecting light related to one or more images (e.g., scenes) within a field of view onto an image sensor. The operational control flow 250 can be performed by a camera system having a camera lens system and a camera assembly, such as the camera system 202 having the camera lens system 204 and the camera assembly 206 as described above FIG. 2A

[0040] At operation 252, the operational control flow 250 can steer a center of the camera lens system toward a periphery of the image sensor of the camera assembly to direct light captured by the center of the camera lens system toward the periphery or edge of the image sensor. In some embodiments, the operational control flow 250 can change an orientation or position of the camera lens system relative to the camera assembly, e.g., tilt, shift, and / or rotate. For example, the operational control flow 250 can steer an orientation or position of a center of the camera lens system (e.g., a center of a super-wide lens such as a fisheye lens or rectilinear lens) relative to the image sensor. In this example, the operational control flow 250 can steer the orientation or position of the center of the camera lens system toward a periphery (e.g., edge) of the image sensor to focus light captured by the center of the camera lens system toward the periphery of the image sensor. In some embodiments, the operational control flow 250 can focus light captured from, e.g., one or more images, toward the periphery of the image sensor.

[0041] At operation 254, the operational control flow 250 can focus light captured by the camera lens system non-uniformly onto the image sensor about the periphery of the image sensor according to operation 252. In some embodiments, the operational control flow 250 can direct light captured by the camera lens system heterogeneously (e.g., non-uniformly) onto the image sensor about an approximate center of the image sensor according to operation 252. In these embodiments, the angular distribution of light according to operation 252 can be characterized as non-uniform across the image sensor as compared to conventional super-wide lenses that project light uniformly as described above. For example, the operational control flow 250 can focus light onto the image sensor according to operation 252 to be more concentrated near a center of the image sensor as compared to a periphery of the image sensor. In some embodiments, the operational control flow 250 can concentrate light near a center of the image sensor to project more detail of an image, e.g., more detail of a scene, near the center of the image sensor.

[0042] Exemplary camera lens system that can be implemented within an exemplary camera system

[0043] ​FIG. 3A and FIG. 3B A simplified block diagram of an exemplary camera lens system that can be implemented within an exemplary camera system in accordance with some example embodiments of the present disclosure is illustrated. In FIG. 3A the exemplary embodiment shown in FIG. 3, camera lens system 302 projects light related to one or more images (e.g., scenes) within its field of view onto image sensor 304. As will be described in further detail below, camera lens system 302 can direct light toward image sensor 304 to provide a heterogeneous (e.g., non-uniform) light distribution on image sensor 304. Camera lens system 302 and image sensor 304 can represent exemplary embodiments of camera lens system 204 and image sensor 212, respectively, as described above in FIG. 2A FIG. 2.

[0044] Camera lens system 302 will be described in further detail below with respect to exemplary ray tracing of light rays 350.1 through 350.n onto image sensor 304. However, it should be noted that the exemplary ray tracing shown in FIG. 3A is for illustrative purposes only. Those skilled in the relevant art will recognize that light rays 350.1 and 350.n can differ from those shown in FIG. 3A FIG. 3. As shown in FIG. 3A FIG. 3, camera lens system 302 can capture light rays 350.1 through 350.n within its field of view. In some embodiments, light rays 350.1 through 350.n can be reflected from one or more physical objects within a scene, for example, within its field of view. In the exemplary embodiment shown in FIG. 3A FIG. 3, light rays 350.1 through 350.n can be characterized as having different angles of incidence with respect to camera lens system 302. In some embodiments, among light rays 350.1 through 350.n, light rays closest to the periphery or edge of the field of view of camera lens system 302 (e.g., light ray 350.1 and light ray 350.n) can be characterized as having the largest angles of incidence, for example, approximately one-half of the field of view of camera lens system 302. For example, camera lens system 302 can have a field of view of one-hundred sixty (160) degrees. In this example, light ray 350.1 and light ray 350.n, as shown in FIG. 3A FIG. 3, can be characterized as having angles of incidence of approximately eighty (80) degrees with respect to camera lens system 302. In some embodiments, among light rays 350.1 through 350.n, an intermediate light ray (e.g., light ray 350.5) can be characterized as having the smallest angle of incidence, for example, approximately zero (0) degrees. In these embodiments, the intermediate light ray can be characterized as propagating parallel to camera lens system 302.

[0045] After capturing light rays 350.1 through 350.n, camera lens system 302 can focus (e.g., converge) light rays 350.1 through 350.n using a simple single lens of transparent material; however, as will be apparent to one skilled in the relevant art, more complex composite lenses of transparent materials, such as doublets, triplets, and / or achromatic lenses, can be used without departing from the spirit and scope of the present disclosure. In these embodiments, the transparent material can include, for example, glass, crystal, and / or plastic (such as acrylic). In some embodiments, these complex composite lenses can be configured and arranged to form an ultra-wide-angle lens, such as a fisheye lens that produces strong visual distortion intended to create one or more hemispherical images, and / or a rectilinear lens that produces one or more images in which straight features (such as the edge of a building wall) appear straight rather than curved as in a fisheye lens, with little or no barrel or pincushion distortion.

[0046] After being focused by camera lens system 302, light rays 350.1 through 350.n may exit camera lens system 302 to provide light rays 352.1 through 352.n to image sensor 304. FIG. 3A In the exemplary embodiment shown in , the camera lens system 302 can angularly distribute the light rays 352.1 through 352.n heterogeneously (e.g., non-uniformly) across the image sensor 304. For example, the angular distribution of the light rays 352.1 through 352.n can be characterized as non-uniform across the image sensor 304 compared to the light rays 354.1 through 354.n exiting a conventional ultra-wide angle lens (e.g., the conventional fisheye lens described above). In this example, the conventional light rays 354.1 through 354.n can be characterized as uniformly distributed across the image sensor 304. FIG. 3B As shown in FIG, regular rays 354.1 through 354.n (for convenience, simply referred to as regular rays 354) may be evenly distributed around a central ray corresponding to an intermediate ray (e.g., ray 350.5) among rays 350.1 through 350.n. In some embodiments, regular rays 354 may be considered to be evenly or equidistantly spaced from one another around the central ray of image sensor 304. FIG. 3BAs shown in FIG. 3, light rays 352.1-352.n (referred to simply as light rays 352 for convenience) can be non-uniformly distributed about a central light ray corresponding to an intermediate light ray (e.g., light ray 350.5) among light rays 350.1-350.n. In some embodiments, light rays 352.1-352.n can be considered to be non-uniformly or differently spaced from one another about the central light ray on image sensor 304. In these embodiments, light rays 352 can be more concentrated near the center of image sensor 304 as compared to the periphery or edge of image sensor 304. In these embodiments, the pixels of image sensor 304 can be distributed among image sensor 304 to provide a first pixel density, e.g., seventy (70) pixels per degree (PPD), at the center of image sensor 304 and gradually transition to a second pixel density, e.g., one hundred forty (140) pixels per degree (PPD), near the periphery of image sensor 304. In these embodiments, the pixels of image sensor 304 can gradually transition from the first pixel density to the second pixel density linearly (e.g., uniformly) and / or non-linearly (e.g., non-uniformly).

[0047] In some embodiments, image sensor 304 can be characterized as having a lower angular resolution at the center of image sensor 304 as compared to the periphery of image sensor 304 because, as shown in FIG. 3, more of light rays 352.1-352.n are captured by image sensor 304 near the center of image sensor 304. FIG. 3A and FIG. 3B In some embodiments, image sensor 304 can be characterized as having a lower angular resolution at the center of image sensor 304 as compared to the periphery of image sensor 304 because, as shown in FIG. 3, more of light rays 352.1-352.n are captured by image sensor 304 near the center of image sensor 304. FIG. 3B As shown in FIG. 3, light rays 352.1-352.n (referred to simply as light rays 352 for convenience) can be non-uniformly distributed about a central light ray corresponding to an intermediate light ray (e.g., light ray 350.5) among light rays 350.1-350.n. In some embodiments, light rays 352.1-352.n can be considered to be non-uniformly or differently spaced from one another about the central light ray on image sensor 304. In these embodiments, light rays 352 can be more concentrated near the center of image sensor 304 as compared to the periphery or edge of image sensor 304. In these embodiments, the pixels of image sensor 304 can be distributed among image sensor 304 to provide a first pixel density, e.g., seventy (70) pixels per degree (PPD), at the center of image sensor 304 and gradually transition to a second pixel density, e.g., one hundred forty (140) pixels per degree (PPD), near the periphery of image sensor 304. In these embodiments, the pixels of image sensor 304 can gradually transition from the first pixel density to the second pixel density linearly (e.g., uniformly) and / or non-linearly (e.g., non-uniformly).

[0048] Exemplary camera lens housing that can be implemented within an exemplary camera system

[0049] FIG. 4A and FIG. 4B FIG. 3 illustrates a simplified block diagram of an exemplary camera lens housing that can be implemented within an exemplary camera system in accordance with some example embodiments of the present disclosure. In FIG. 4A and FIG. 4BIn the exemplary embodiment shown in FIG. 4, the camera lens housing 402 projects light onto the image sensor 404. As will be described in further detail below, the camera lens housing 402 can change an orientation or position of the camera lens housing 402 relative to the image sensor 404, e.g., tilt, shift, and / or rotate. Accordingly, the camera lens housing 402 can turn the orientation or position of the center of the camera lens housing 402 to focus light captured by the camera lens housing 402 toward the periphery (e.g., edge) of the image sensor 404. The camera lens housing 402 and the image sensor 404 can represent exemplary embodiments of the camera lens housing and the image sensor 212 of the camera lens system 204 as described above in FIG. 2. FIG. 2A

[0050] In the exemplary embodiment shown in FIG. 4, the camera lens housing 402 projects light onto the image sensor 404. As will be described in further detail below, the camera lens housing 402 can change an orientation or position of the camera lens housing 402 relative to the image sensor 404, e.g., tilt, shift, and / or rotate. Accordingly, the camera lens housing 402 can turn the orientation or position of the center of the camera lens housing 402 to focus light captured by the camera lens housing 402 toward the periphery (e.g., edge) of the image sensor 404. The camera lens housing 402 and the image sensor 404 can represent exemplary embodiments of the camera lens housing and the image sensor 212 of the camera lens system 204 as described above in FIG. 2. FIG. 4A FIG. 4A In the exemplary embodiment shown in FIG. 4, the camera lens housing 402 can be implemented to form a view angle control lens, such as a shift lens or a tilt-shift lens. As shown in FIG. 4, the camera lens housing 402 can capture light rays 450 within its field of view. In some embodiments, the light rays 450 can be reflected from one or more physical objects within, for example, a scene. After capturing the light rays 450, the camera lens housing 402 can focus (e.g., converge) the light rays 450 using a simple single lens of transparent material; however, as will be apparent to those of ordinary skill in the relevant art without departing from the spirit and scope of the present disclosure, it is possible to use more complex compound lenses of transparent material, such as doublet lenses, triplet lenses, and / or achromatic lenses. In these embodiments, the transparent material can include glass, crystal, and / or plastic (e.g., such as acrylic). In some embodiments, these complex compound lenses can be configured and arranged to form a super-wide angle lens, for example, such as a fisheye lens that produces a strong visual distortion intended to create one or more hemispherical images, and / or a rectilinear lens that produces one or more images with little or no barrel or pincushion distortion in which straight-line features, such as the edges of a building wall, appear straight rather than curved as in a fisheye lens.

[0051] After being focused by the camera lens housing 402, the light rays 450 can exit the camera lens housing 402 to provide light rays 452.1 and / or light rays 452.2 toward the image sensor 404. In some embodiments, the camera lens housing 402 can focus the light rays 450 captured from one or more images (e.g., a scene) to provide the light rays 452.1 corresponding to the one or more images to the image sensor 404. In some embodiments, the camera lens housing 402 can focus the light rays 452.1 onto the center of the image sensor 404. As shown in FIG. 4, the light rays 452.1 can be focused onto the center of the image sensor 404. In some embodiments, the camera lens housing 402 can focus the light rays 452.2 onto the periphery (e.g., edge) of the image sensor 404. As shown in FIG. 4, the light rays 452.2 can be focused onto the periphery of the image sensor 404. FIG. 4B ​​As shown in FIG. 4A, the center of camera lens housing 402 can be configured and arranged to be oriented or positioned relative to image sensor 404 to project the center 454.1 of the simple single lens and / or compound lens of camera lens housing 402 to the center of image sensor 404. In some embodiments, the light rays 452.1 projected onto image sensor 404 can be reconstructed into one or more images that can be projected onto a three-dimensional media plane (e.g., such as three-dimensional media plane 102) in a substantially similar manner as described above in FIG. 1A and FIG. 1B FIGS. 4B and 4C. In these embodiments, the one or more images that can be projected onto the three-dimensional media plane can be characterized as having their highest optical image quality (e.g., resolution) at the top of the three-dimensional media plane (e.g., within the conventional primary viewing segment 112 as described above).

[0052] Alternatively or additionally, camera lens housing 402 can also focus light rays 450 captured from, for example, a scene to provide light rays 452.2 corresponding to one or more images to image sensor 404. In some embodiments, camera lens housing 402 can focus light rays 452.2 toward the periphery (e.g., edges) of image sensor 404. In these embodiments, camera lens housing 402 can change the orientation or position of the center of camera lens housing 402 relative to image sensor 404, for example, tilt, shift, and / or rotate. For example, camera lens housing 402 can turn the orientation or position of the center of camera lens housing 402 relative to image sensor 404. In this example, camera lens housing 402 can turn the orientation or position of the center of camera lens housing 402 relative to image sensor 404 to direct light rays 452.2 toward the periphery (e.g., edges) of image sensor 404. As shown in FIG. 4D, camera lens housing 402 can turn the orientation or position of the center of camera lens housing 402 by a height H to shift the projection of light rays 452.2 on image sensor 404 by a height h. In some embodiments, height H is approximately one-to-one with height h. In these embodiments, the orientation or position of the center of camera lens housing 402 can be turned relative to the image circle projected by camera lens housing 402 that is related to the coverage of image sensor 404. For example, if the image circle projected by camera lens housing 402 is ten (10) mm larger than the height of image sensor 404, then a turn of five (5) mm can be implemented. In this example, any additional turning of the orientation or position of the center of camera lens housing 402 beyond five (5) mm is often not beneficial. FIG. 4A

[0053] As shown in FIG. 4D, camera lens housing 402 can turn the orientation or position of the center of camera lens housing 402 by a height H to shift the projection of light rays 452.2 on image sensor 404 by a height h. In some embodiments, height H is approximately one-to-one with height h. In these embodiments, the orientation or position of the center of camera lens housing 402 can be turned relative to the image circle projected by camera lens housing 402 that is related to the coverage of image sensor 404. For example, if the image circle projected by camera lens housing 402 is ten (10) mm larger than the height of image sensor 404, then a turn of five (5) mm can be implemented. In this example, any additional turning of the orientation or position of the center of camera lens housing 402 beyond five (5) mm is often not beneficial.

[0053] As shown in FIG. 4D, camera lens housing 402 can turn the orientation or position of the center of camera lens housing 402 by a height H to shift the projection of light rays 452.2 on image sensor 404 by a height h. In some embodiments, height H is approximately one-to-one with height h. In these embodiments, the orientation or position of the center of camera lens housing 402 can be turned relative to the image circle projected by camera lens housing 402 that is related to the coverage of image sensor 404. For example, if the image circle projected by camera lens housing 402 is ten (10) mm larger than the height of image sensor 404, then a turn of five (5) mm can be implemented. In this example, any additional turning of the orientation or position of the center of camera lens housing 402 beyond five (5) mm is often not beneficial. FIG. 4BAs shown in FIG, the center of the camera lens housing 402 can be configured and arranged to be oriented or positioned relative to the image sensor 404 to shift the center 454.2 of the simple single lens and / or compound lens of the camera lens housing 402 by a height h compared to the center 454.1 on the image sensor 404. In some embodiments, the light rays 452.2 projected onto the image sensor 404 can be reconstructed into one or more images, which can be arranged in the same manner as above. FIG. 1A and FIG. 1B In these embodiments, one or more images that can be projected onto a three-dimensional media plane can be characterized such that their highest optical image quality (e.g., resolution) is along the interior of the three-dimensional media plane (e.g., on the top). FIG. 1A and FIG. 2B In some embodiments, as described above, FIG. 1A and 2B The viewer primary viewing segment 104 described in the above can be characterized as being displaced along the polar angle relative to the conventional primary viewing segment 112 described above. In these embodiments, the angular difference or displacement along the polar angle between the conventional primary viewing segment 112 and the viewer primary viewing segment 104 can be expressed as:

[0054]

[0055] Among them, shift θ represents the angular difference or displacement between the normal primary viewing segment 112 and the viewer primary viewing segment 104 along the polar angle θ, height h As above FIG. 4A and FIG. 4B The height h, l expressed in millimeters (mm) described in sensor represents the vertical or horizontal dimension of the image sensor 404 expressed in millimeters (mm) assuming a square image sensor, and fov represents the field of view of the simple single lens and / or compound lens of the camera lens housing 402. For example, a shift of fifteen (15) millimeters (mm) between the center of the camera lens housing 402 and the center of the image sensor 404 provides a thirty-two (32) degree shift along the polar angle θ between the conventional primary viewing section 112 and the viewer primary viewing section 104 for a 75 millimeter (mm) square image sensor, and provides a one hundred sixty (160) degree field of view for the simple single lens and / or compound lens of the camera lens housing 402.

[0056] Exemplary camera system

[0057] FIG. 5A andFIG. 5B FIG. 1 illustrates a simplified block diagram of an example camera system, in accordance with some example embodiments of the present disclosure. In FIG. 5A In the example embodiment shown in FIG. 2, camera lens system 500 can project light captured by camera lens system 500 onto image sensor 506. As FIG. 5A As shown in FIG. 3, camera lens system 500 can include camera lens system 502 to direct light captured from, for example, a scene onto image sensor 506. Camera lens system 502 can direct light toward image sensor 506 so as to provide a heterogeneous (e.g., non-uniform) distribution of light onto image sensor 506 in a substantially similar manner as camera lens system 302 described above in FIG. 3A and FIG. 3B As shown in FIG. 4, camera lens system 500 can include camera lens housing 504 to direct light captured by camera lens system 502 onto image sensor 506. Camera lens housing 504 can change the orientation or position of camera lens system 502 relative to image sensor 506, for example, tilt, shift, and / or rotate, in a substantially similar manner as camera lens housing 402 described above in FIG. 5A and FIG. 4A As shown in FIG. 5, camera lens system 502 can capture light rays 550 within its field of view in a substantially similar manner as camera lens system 302 described above in FIG. 4B and FIG. 3A As shown in FIG. 6, camera lens system 502 can angularly distribute light rays 552.1 across image sensor 506 heterogeneously (e.g., non-uniformly) in a substantially similar manner as camera lens system 302 described above in FIG. 3B and FIG. 4A As shown in FIG. 7, a center of camera lens housing 504 can be configured and arranged to tilt camera lens system 502 in a substantially similar manner as camera lens housing 402 described above in FIG. 4B and As shown in FIG. 8, a center of camera lens housing 504 can be configured and arranged to shift camera lens system 502 in a substantially similar manner as camera lens housing 402 described above in

[0058] and FIG. 5A As shown in FIG. 9, a center of camera lens housing 504 can be configured and arranged to rotate camera lens system 502 in a substantially similar manner as camera lens housing 402 described above in FIG. 3A and FIG. 3B As shown in FIG. 10, camera lens system 502 can capture light rays 550 within its field of view in a substantially similar manner as camera lens system 302 described above in FIG. 5A and FIG. 3A As shown in FIG. 11, camera lens system 502 can angularly distribute light rays 552.1 across image sensor 506 heterogeneously (e.g., non-uniformly) in a substantially similar manner as camera lens system 302 described above in FIG. 3B and FIG. 5B As shown in FIG. 12, a center of camera lens housing 504 can be configured and arranged to tilt camera lens system 502 in a substantially similar manner as camera lens housing 402 described above in FIG. 4A and FIG. 4BThe center 554.1 of the camera lens system 502 is oriented or positioned relative to the image sensor 506 in substantially similar fashion as described above in FIG. 5B The camera lens system 502 can further be shown in FIG. 3A and FIG. 3B The camera lens system 302 described above in

[0059] Alternatively or additionally, the camera lens housing 504 can focus the light rays 550 captured from, for example, a scene to provide light rays 552.2 corresponding to one or more images to the image sensor 506. In FIG. 5A The camera lens housing 504 can change the orientation or position of the camera lens system 502 relative to the image sensor 506, for example, tilt, shift, and / or rotate, in substantially similar fashion as described above in FIG. 4A and FIG. 4B The camera lens housing 504 can turn the orientation or position of the center of the camera lens system 502 relative to the image sensor 506 in this example. The camera lens housing 504 can turn the orientation or position of the center of the camera lens system 502 in substantially similar fashion as described above in FIG. 4A and FIG. 4B The camera lens housing 504 can turn the orientation or position of the center of the camera lens system 502 to direct the light rays 452.2 toward the periphery (e.g., edge) of the image sensor 506 in substantially similar fashion as described above in FIG. 4B The center of the camera lens housing 504 can be configured and arranged to be oriented or positioned relative to the image sensor 506 in substantially similar fashion as described above in FIG. 4A and FIG. 4B The center 554.2 of the camera lens system 502 is oriented or positioned relative to the image sensor 506 in substantially similar fashion as described above in FIG. 5B The camera lens system 502 can be specially manufactured to direct the light rays 552.2 to be distributed heterogeneously (e.g., non-uniformly) around the periphery of the image sensor 506 onto the image sensor 506 in further shown in FIG. 3A and FIG. 3BLight rays 552.2 are angularly distributed toward the periphery of image sensor 506 heterogeneously (e.g., non-uniformly) in a substantially similar manner as described in the Background. For example, camera lens system 502 can focus light rays 552.2 onto image sensor 506 so as to be more concentrated near the periphery of image sensor 502 than the center of image sensor 506. In some embodiments, camera lens system 502 can concentrate light near the periphery of image sensor 502 so as to project more detail of one or more images, e.g., more detail of a scene, near the periphery of image sensor 502. In these embodiments, camera lens system 502 can concentrate light near the periphery of image sensor 506 at a first pixel density, e.g., seventy (70) pixels per degree (PPD), and gradually transition to a second pixel density at the center of image sensor 506, e.g., one hundred forty (140) pixels per degree (PPD). In these embodiments, the pixels of image sensor 506 can gradually transition from the first pixel density to the second pixel density linearly (e.g., uniformly) and / or non-linearly (e.g., non-uniformly).

[0060] Exemplary image projection system for projecting captured images onto exemplary venues

[0061] FIG. 6 A simplified block diagram of an exemplary image projection system is illustrated in accordance with some example embodiments of the present disclosure. As described above, an image capture system, such as image capture system 200 described above in the Background FIG. 2A may capture one or more images that can be projected onto a three-dimensional media plane of a venue, such as three-dimensional media plane 102 of venue 100 described above in the Background FIG. 1A and FIG. 1B In the example embodiment shown in FIG. 6 , image projection system 600 can transform one or more images from two-dimensions to three-dimensions for projection onto a three-dimensional media plane. As will be described in further detail below, image projection system 600 can utilize a kernel-based sampling technique to project one or more picture elements (also referred to as pixels) of a three-dimensional media plane onto one or more corresponding two-dimensional points on one or more images. In these embodiments, the kernel-based sampling technique subsequently weights and accumulates color information of one or more pixels from one or more images located near one or more corresponding two-dimensional points on one or more images to interpolate color information (e.g., luminance and / or chrominance components of a YUV color model and / or red, green, and / or blue components of an RGB color model) of a pixel of a three-dimensional media plane. As shown in FIG. 6 , image projection system 600 can include image recording system 208 that can be communicatively coupled to image processing server 604 and venue 606 via communication network 608. While image projection system 600 is shown inFIG. 6 The environment is shown as including a plurality of discrete devices, but one of skill in the relevant art will recognize that one or more of these devices can be combined together without departing from the spirit and scope of the present disclosure. For example, the image recording system 208 and the image processing server 604 can be combined into a single discrete device without the need for the communications network 608 without departing from the spirit and scope of the present disclosure, as will be apparent to one of skill in the relevant art.

[0062] As noted above, the image recording system 208 can store one or more digital image signals and / or one or more images provided by an image capture system, such as the image capture system 200 described in FIG. 2A As noted above, the image recording system 208 can store one or more digital image signals and / or one or more images provided by an image capture system, such as the image capture system 200 described in FIG. 6 As noted above, the image recording system 208 can store one or more digital image signals and / or one or more images provided by an image capture system, such as the image capture system 200 described in FIG. 1A and FIG. 1B As noted above, the image recording system 208 can store one or more digital image signals and / or one or more images provided by an image capture system, such as the image capture system 200 described in

[0063] The image processing server 604 includes one or more computer systems, exemplary embodiments of which will be described in further detail below, to retrieve one or more images stored in the image recording system 208. Alternatively or additionally, the image processing server 604 can also reconstruct one or more images from one or more digital image signals stored in the image recording system 208. In some embodiments, the image processing server 604 can implement one or more digital image processing techniques, also referred to as digital picture processing techniques, to process one or more digital image signals stored in the image recording system 208 in order to reconstruct one or more images from the one or more digital image signals. In some embodiments, the one or more digital image processing techniques can include decoding, demosaicing, defective pixel removal, white balancing, noise reduction, color translation, tone reproduction, compression, removal of system noise, dark frame subtraction, optical correction, contrast manipulation, unsharp masking, and / or any other suitable well-known digital image processing techniques, as will be apparent to one of skill in the relevant art, without departing from the spirit and scope of the present disclosure.

[0064] After retrieving one or more images and / or reconstructing one or more images from one or more digital image signals, the image processing server 604 can mathematically transform two-dimensional coordinates of the one or more images into three-dimensional coordinates of the venue 606, as will be described in further detail below, to enable the one or more images to be projected onto the venue 606. In FIG. 6In the exemplary embodiments illustrated in FIG. 6, the image processing server 604 can mathematically transform the two-dimensional coordinates of the one or more images into the three-dimensional coordinates of the venue 606 using a kernel-based sampling technique. In some embodiments, the kernel-based sampling technique projects the three-dimensional coordinates of the venue 606 pixels into the two-dimensional image space of the one or more images to effectively transform the three-dimensional coordinates of the venue 606 into two-dimensional coordinates of two-dimensional points projected onto the one or more images. In these embodiments, the kernel-based sampling technique can convert the three-dimensional coordinates of the venue 606 into the two-dimensional image space of the one or more images. This conversion can spatially align the three-dimensional coordinates of the venue 606 with the two-dimensional image space of the one or more images. For example, the kernel-based sampling technique can spatially align the top of the venue 606 with the top of the two-dimensional image space of the one or more images.

[0065] After mathematically transforming the two-dimensional coordinates of the one or more images, the kernel-based sampling technique statistically interpolates the color information (e.g., luminance and / or chrominance components of a YUV color model and / or red, green, and / or blue components of an RGB color model) of the venue 606 pixels in the one or more images. In some embodiments, the kernel-based sampling technique can statistically interpolate the color information of the venue 606 pixels based on the color information of the one or more images pixels. In these embodiments, the kernel-based sampling technique can statistically interpolate the color information of the venue 606 pixels by weighting and accumulating the color information of the one or more images pixels near the two-dimensional points projected onto the one or more images in the one or more images.

[0066] After interpolating the color information of the venue 606 pixels, the image processing server 604 can provide the color information to the venue 606 to project the images onto the venue 606. In some embodiments, the image processing server 604 can generate a quadruple for the venue 606 pixels that includes the three-dimensional coordinates of the venue 606 pixels and the statistically interpolated color information of the venue 606 pixels from the one or more images. In these embodiments, the image processing server 604 can provide the quadruple to the venue 606 to project the images onto the venue 606. FIG. 6In the exemplary embodiment shown in , venue 606 can represent a three-dimensional structure, such as a hemispherical structure (also known as a hemispherical dome). In some embodiments, the hemispherical structure can include one or more visual displays dispersed across the interior or soffit of the hemispherical structure, often referred to as a three-dimensional media plane. In these embodiments, the one or more visual displays can include a series of rows and a series of columns of picture elements (also known as pixels) that form the three-dimensional media plane. In these embodiments, the pixels can be implemented using, for example, one or more light emitting diode (LED) displays, one or more organic light emitting diode (OLED) displays, and / or one or more quantum dot (QD) displays. For example, the three-dimensional media plane can include a 19,000×13,500 LED visual display that wraps around the interior of the three-dimensional structure to form a visual display of approximately 160,000 square feet. In some embodiments, such as during an event, venue 600 can illuminate the pixels of venue 606 based on color information to project one or more images onto the three-dimensional media plane. In these embodiments, one or more images can be projected onto the three-dimensional media plane during the event to enhance the visual experience of the audience while watching the event. FIG. 7 In the exemplary embodiment shown in FIG, the three-dimensional media plane may include a primary viewing zone for viewers with the highest optical image quality located along the interior or soffit of the three-dimensional media plane, such as the one shown above. FIG. 1A and FIG. 1B In some embodiments, the main viewing area 104 is the same as the main viewing area 104 described in FIG. FIG. 1A and FIG. 1B In a manner substantially similar to the viewer primary viewing section 104 shown in FIG, the viewer primary viewing section can be considered a hemispherical structure located approximately halfway between the top and base of the three-dimensional media plane. FIG. 1A and FIG. 1B In a manner substantially similar to the viewer primary viewing segment 104 illustrated in FIG, the viewer primary viewing segment can be characterized as having the highest optical image quality (e.g., resolution) compared to other viewing segments of the three-dimensional media plane. FIG. 1A and FIG. 1B In a manner substantially similar to the viewer primary viewing zone 104 illustrated in FIG, the optical image quality of one or more images decreases along the interior of the three-dimensional media plane from the highest optical image quality in the viewer primary viewing zone toward another viewing zone diametrically opposite the viewer primary viewing zone.

[0067] Exemplary kernel-based sampling technique that can be implemented within an exemplary image projection system

[0068] FIG. 7A flowchart of an exemplary kernel-based sampling technique that can be implemented within an exemplary image projection system is illustrated in accordance with some example embodiments of the present disclosure. The present disclosure is not limited to this operational description. Rather, it will be apparent to one of ordinary skill in the relevant art that other operational control flows are within the scope and spirit of the present disclosure. The following discussion describes an exemplary operational control flow 700 for mathematically transforming two-dimensional coordinates (uv.xl, uv.yl), (uv.x2, uv.y2)... (uv.x m ,uv.y m ) of pixels of an image into three-dimensional coordinates (pos.xl, pos.yl, pos.zl), (pos.x2, pos.y2, pos.z2)... (pos.x n ,pos.y n ,pos.z n ) of a three-dimensional media plane of a three-dimensional venue (such as venue 100 described above in FIG. 1A and FIG. 1B , and / or venue 606 described above in FIG. 6 ). For convenience, the two-dimensional coordinates (uv.xl, uv.yl), (uv.x2, uv.y2)... (uv.x m ,uv.y m ) are collectively referred to as two-dimensional coordinates uv.x, uv.y, and the three-dimensional coordinates (pos.xl, pos.yl, pos.zl), (pos.x2, pos.y2, pos.z2)... (pos.x n ,pos.y n ,pos.z n ) are collectively referred to as three-dimensional coordinates pos.x, pos.y, and pos.z. For example, operational control flow 700 can be executed by one or more computer systems (such as, for example, image processing server 604 described above in FIG. 6 .

[0069] At operation 702, operational control flow 700 projects the three-dimensional coordinates pos.x, pos.y, and pos.z of the three-dimensional media plane pixels onto the image to effectively transform the three-dimensional coordinates pos.x, pos.y, and pos.z of the three-dimensional media plane pixels into two-dimensional coordinates (UV.xl, UV.yl), (UV.x2, UV.y2)... (UV.x n ,UV.y n ) of two-dimensional points projected on the image. For convenience, the two-dimensional coordinates (UV.xl, UV.yl), (UV.x2, UV.y2)... (UV.x n ,UV.y n) are collectively referred to as two-dimensional coordinates UV.x, UV.y.

[0070] At operation 704, the operational control flow 700 statistically interpolates color information (e.g., luminance and / or chrominance components of a YUV color model and / or red, green, and / or blue components of an RGB color model) of pixels of the three-dimensional media plane from the image according to operation 702. In some embodiments, the operational control flow 700 may statistically interpolate the color information of the pixels of the three-dimensional media plane according to operation 702 based on the pixel color information of the image in operation 702. In these embodiments, the operational control flow 700 may statistically interpolate the color information of the pixels of the three-dimensional media plane according to operation 702 according to operation 702 by weighting and accumulating color information of pixels of the image near the two-dimensional point projected on the image according to operation 702. In some embodiments, the weighting may be a distance-based weighting of the color information of pixels of the image according to operation 702 near the two-dimensional point projected on the image according to operation 702. For example, pixels in the image according to operation 702 that are closer to the two-dimensional point projected on the image according to operation 702 may be weighted more heavily than pixels that are farther from the two-dimensional point projected on the image according to operation 702. In some embodiments, if the distance between a two-dimensional point projected on the image according to operation 702 and nearby pixels of the image can be considered as a random variable, then without departing from the spirit and scope of the present disclosure, the operation control flow 700 can weight the color information of the nearby pixels of the image according to a probability density function (such as a Gaussian distribution, a normal distribution, a standard normal distribution, a Student's t distribution, a chi-square distribution, a continuous uniform distribution and / or any other well-known probability density function, which will be apparent to those skilled in the relevant art).

[0071] At operation 706, the control flow 700 is operated to FIG. 6 The color information of the pixels is provided to the arena for projection onto the arena in a substantially similar manner as described in .

[0072] FIG. 8 FIGURE 1 illustrates a kernel-based sampling technique that can be implemented within an exemplary projection system according to some exemplary embodiments of the present disclosure. FIG. 8 The discussion will be further described as above FIG. 6 The kernel-based sampling techniques described in and / or as above FIG. 7 The operational control flow described in 700. FIG. 8In the exemplary embodiment shown in , the kernel-based sampling technique 800 mathematically transforms the two-dimensional coordinates of the image 802 into the three-dimensional coordinates of the three-dimensional media plane of the three-dimensional venue 804. When executed by one or more computing devices, processors, controllers, or other electrical, mechanical, and / or electromechanical devices that will be apparent to those skilled in the relevant art(s), the kernel-based sampling technique 800 can mathematically transform the two-dimensional coordinates of pixels 806.1 through 806.m of the image 802 into the three-dimensional coordinates of pixels 808.1 through 808.n of the three-dimensional media plane, as described in further detail below. In some embodiments, the kernel-based sampling technique 800 can represent the above FIG. 6 The kernel-based sampling techniques described in and / or as above FIG. 7 An exemplary embodiment of the operation control flow 700 described in FIG. FIG. 1A and FIG. 1B The location 100 described above and / or FIG. 6 and / or FIG. 7 An exemplary embodiment of a three-dimensional media plane is described in .

[0073] exist FIG. 8 In the exemplary embodiment shown in FIG, the kernel-based sampling technique 800 may be used to sample the two-dimensional coordinates (uv.x1, uv.y1), (uv.x2, uv.y2) ... (uv.x m ,uv.y m ) is mathematically transformed into the three-dimensional coordinates of the three-dimensional media plane (pos.x1, pos.y1, pos.z1), (pos.x2, pos.y2, pos.z2)…(pos.x n ,pos.y n ,pos.z n ), so that the image 802 can be projected onto the three-dimensional media plane. For convenience, the two-dimensional coordinates (uv.x1, uv.y1), (uv.x2, uv.y2) ... (uv.x m ,uv.y m ) are collectively referred to as two-dimensional coordinates uv.x, uv.y, three-dimensional coordinates (pos.x1, pos.y1, pos.z1), (pos.x2, pos.y2, pos.z2)…(pos.x n ,pos.y n ,pos.z n ) are collectively referred to as the three-dimensional coordinates pos.x, pos.y and pos.z. FIG. 8As shown in FIG, the kernel-based sampling technique 800 can project the three-dimensional coordinates pos.x, pos.y, and pos.z of the pixels 808.1 to 808.n of the three-dimensional media plane onto the two-dimensional space of the image 802 to effectively transform the three-dimensional coordinates pos.x, pos.y, and pos.z of the pixels 808.1 to 808.n into two-dimensional coordinates (UV.x1, UV.y1), (UV.x2, UV.y2) ... (UV.x n ,UV.y n ). For convenience, the two-dimensional coordinates (UV.x1, UV.y1), (UV.x2, UV.y2)…(UV.x n ,UV.y n ) are collectively referred to as the two-dimensional coordinates UV.x, UV.y projected onto the two-dimensional space of the image 802.

[0074] After projecting the three-dimensional coordinates pos.x, pos.y, and pos.z of pixels 808.1 through 808.n onto the three-dimensional media plane, the kernel-based sampling technique 800 statistically interpolates color information (e.g., luminance and / or chrominance components of a YUV color model and / or red, green, and / or blue components of an RGB color model) of pixels 808.1 through 808.n from the image 802. In some embodiments, the kernel-based sampling technique 800 may statistically interpolate the color information of pixels 808.1 through 808.n based on the color information of pixels 806.1 through 806.m. In these embodiments, the kernel-based sampling technique 800 may statistically interpolate the color information of pixels 808.1 through 808.n by weighting and accumulating the color information of pixels 806.1 through 806.m near two-dimensional points 810.1 through 810.n.

[0075] like FIG. 8As shown in FIG. 8, the kernel-based sampling technique 800 can weight color information of the pixels 806.1-806.m near the two-dimensional points 810.1-810.n. In some embodiments, the kernel-based sampling technique 800 can identify the pixels 806.1-806.m near the two-dimensional points 810.1-810.n. In these embodiments, the pixels 806.1-806.m near the two-dimensional points 810.1-810.n can be located within a region of interest (ROI) of the image 802 (also referred to as the sampling kernel spaces 812.1-812.r). Generally, without departing from the spirit and scope of the present disclosure, the sampling kernel spaces 812.1-812.r can be any geometric region within the two-dimensional space of the image 802 that includes one or more of the pixels 806.1-806.m, as will be apparent to those of skill in the relevant art. In some embodiments, for example, the any geometric region can include a closed geometric region, such as a regular curve (such as a circle or an ellipse), an irregular curve; a regular polygon (such as an equilateral triangle or a square), and / or an irregular polygon (such as a rectangle and / or a parallelogram). Alternatively or additionally, the any geometric region can be related to one or more mathematical functions (for example, such as the Ackley function, the Himmelblau function, the Rastrigin function, the Rosenbrock function (also referred to as the Rosenbrock banana function), and / or the Shekel function). In some embodiments, the sampling kernel spaces 812.1-812.r can be substantially similar to one another. Alternatively, some of the sampling kernel spaces 812.1-812.r can be different from one another. For example, the kernel-based sampling technique 800 can utilize one or more mathematical functions (for example, such as the Rosenbrock function) as the any geometric region for a first sampling kernel space among the sampling kernel spaces 812.1-812.r and a regular curve (for example, such as a circle) as the any geometric region for a second sampling kernel space among the sampling kernel spaces 812.1-812.r. In some embodiments, the any geometric region can be related to the three-dimensional coordinates pos.x, pos.y, and pos.z of the pixels 808.1-808.n of the three-dimensional media plane. In these embodiments, the kernel-based sampling technique 800 can utilize a first any geometric region for a first sampling kernel space when the three-dimensional coordinates pos.x, pos.y, and pos.z of the corresponding pixel are near the top or crown of the three-dimensional media plane, and / or a second any geometric region for a second sampling kernel space when the three-dimensional coordinates pos.x, pos.y, and pos.z of the corresponding pixel are near the bottom or pop of the three-dimensional media plane.

[0076] After identifying the pixels 806.1-806.m within the sampling kernel space 812.1-812.r, the kernel-based sampling technique 800 can weight the color information (e.g., luminance and / or chrominance components of a YUV color model, and red, green, and / or blue components of an RGB color model) of these pixels. In some embodiments, the weighting can be a distance-based weighting of the color information of the pixels 806.1-806.m within the sampling kernel space 812.1-812.r. For example, the pixels 806.1-806.m within the sampling kernel space 812.1-812.r that are closer to the two-dimensional points 810.1-810.n can be weighted more heavily than the pixels 806.1-806.m within the sampling kernel space 812.1-812.r that are farther from the two-dimensional points 810.1-810.n. In some embodiments, without departing from the spirit and scope of the present disclosure, if the distance between the pixels 806.1-806.m within the sampling kernel space 812.1-812.r and the two-dimensional points 810.1-810.n can be considered a random variable, then the kernel-based sampling technique 800 can weight the color information of the pixels 806.1-806.m within the sampling kernel space 812.1-812.r according to a probability density function, such as a Gaussian distribution, a normal distribution, a standard normal distribution, a Student's t-distribution, a chi-squared distribution, a continuous uniform distribution, and / or any other well-known probability density function, as will be apparent to those of ordinary skill in the relevant art.

[0077] Once the color information of the pixels 806.1-806.m within the sampling kernel space 812.1-812.r has been weighted, the kernel-based sampling technique 800 can accumulate the weighted color information of these pixels to statistically interpolate the color information of the pixels 808.1-808.n. In some embodiments, without departing from the spirit and scope of the present disclosure, the kernel-based sampling technique 800 can accumulate the weighted color information of the pixels 806.1-806.m within the sampling kernel space 812.1-812.r to statistically interpolate the color information of the pixels 808.1-808.n according to a probability density function, such as a Gaussian distribution, a normal distribution, a standard normal distribution, a Student's t-distribution, a chi-squared distribution, a continuous uniform distribution, and / or any other well-known probability density function, as will be apparent to those of ordinary skill in the relevant art. FIG. 8In the exemplary embodiment shown in , the kernel-based sampling technique 800 may accumulate the color information of pixels 806.1 to 806.m, which have been weighted as described above, into sampling kernel spaces 812.1 to 812.r to statistically interpolate the color information of two-dimensional points 810.1 to 810.n. In these embodiments, the kernel-based sampling technique 800 may associate the two-dimensional points 810.1 to 810.n projected onto the two-dimensional space of the image 802 with their corresponding pixels among the pixels 808.1 to 808.n on the three-dimensional media plane. Thereafter, the kernel-based sampling technique 800 may associate the color information of the two-dimensional points 810.1 to 810.n with their corresponding pixels among the pixels 808.1 to 808.n to statistically interpolate the color information of the pixels 808.1 to 808.n. In some embodiments, the kernel-based sampling technique 800 may generate a quad for pixels 808 . 1 to 808 . n that includes the three-dimensional coordinates pos.x , pos.y , and pos.z of pixels 808 . 1 to 808 . n and color information of pixels 808 . 1 to 808 . n that has been statistically interpolated from the image 802 .

[0078] FIG. 9 The kernel-based sampling technique that can be implemented in an exemplary projection system according to some exemplary embodiments of the present disclosure is illustrated. FIG. 9 The discussion will be further described as above FIG. 8 An exemplary embodiment of the sampling kernel space of the kernel-based sampling technique 800 described in . FIG. 9 In the exemplary embodiment shown in , the kernel-based sampling technique 900 mathematically transforms the two-dimensional coordinates of the image 902 into the three-dimensional coordinates of the three-dimensional media plane of the three-dimensional venue 904. When executed by one or more computing devices, processors, controllers, or (one or more) electrical, mechanical, and / or electromechanical devices as will be apparent to one skilled in the relevant art(s), the kernel-based sampling technique 900 can mathematically transform the two-dimensional coordinates of pixels 906.1 through 906.m of the image 902 into the three-dimensional coordinates of pixels 908.1 through 908.n of the three-dimensional media plane, as will be described in further detail below. In some embodiments, the kernel-based sampling technique 900 can represent the above FIG. 8 Therefore, the kernel-based sampling technique 900 described in further detail below is similar to the kernel-based sampling technique 800 described above. FIG. 8 The kernel-based sampling technique 800 described in shares many substantially similar features; therefore, only the differences between the kernel-based sampling technique 800 and the kernel-based sampling technique 900 will be described in further detail below.

[0079] like FIG. 9 As shown in the above FIG. 8In a manner substantially similar to the kernel-based sampling technique 800 described above in FIG. 8, the kernel-based sampling technique 900 can project the three-dimensional coordinates pos.x, pos.y, and pos.z of the pixels 908.1 through 908.n of the three-dimensional media plane onto the two-dimensional space of the image 902 to effectively transform the three-dimensional coordinates pos.x, pos.y, and pos.z of the pixels 908.1 through 908.n into the two-dimensional coordinates uv.x, uv.y of the two-dimensional points 910.1 through 910.n projected onto the two-dimensional space of the image 902.

[0080] After projecting the three-dimensional coordinates pos.x, pos.y, and pos.z of the pixels 908.1 through 908.n, the kernel-based sampling technique 900 can perform statistical interpolation on the color information (e.g., luminance and / or chrominance components of a YUV color model and / or red, green, and / or blue components of an RGB color model) of the three-dimensional media plane in the image 902 in a manner substantially similar to the kernel-based sampling technique 800 described above in FIG. 8. However, as shown in FIG. 9, the kernel-based sampling technique 900 can perform statistical interpolation on the color information of the three-dimensional media plane in the image 902 in a manner substantially similar to the kernel-based sampling technique 800 described above in FIG. 8. FIG. 8 FIG. 9 As shown in FIG. 9, the pixels 906.1 through 906.m in the vicinity of the two-dimensional points 910.1 through 910.n can be located within the regions of interest (ROIs) (also referred to as sampling kernel spaces) 912.1 through 912.r of the image 902. As shown in FIG. 9, the kernel-based sampling technique 900 can perform statistical interpolation on the color information of the three-dimensional media plane in the image 902 in a manner substantially similar to the kernel-based sampling technique 800 described above in FIG. 8. FIG. 9 As shown in FIG. 9, the two-dimensional point 910.1 corresponding to the pixel 908.1 can be located within the sampling kernel space 912.1, the two-dimensional point 910.a corresponding to the pixel 908.a can be located within the sampling kernel space 912.b, and / or the two-dimensional point 910.n corresponding to the pixel 908.n can be located within the sampling kernel space 912.n.

[0081] As shown in FIG. 9, the kernel-based sampling technique 900 can perform statistical interpolation on the color information of the three-dimensional media plane in the image 902 in a manner substantially similar to the kernel-based sampling technique 800 described above in FIG. 8. FIG. 9 In the exemplary embodiment shown in FIG. 9, the two-dimensional areas of the sampling kernel spaces 912.1 through 912.r can be related to the distances between the pixels 908.1 through 908.n of the three-dimensional media plane. As shown in FIG. 9, the kernel-based sampling technique 900 can perform statistical interpolation on the color information of the three-dimensional media plane in the image 902 in a manner substantially similar to the kernel-based sampling technique 800 described above in FIG. 8. FIG. 9 ​As shown in FIG. 9, the pixels 908.1 through 908.n can be positioned along a circle or slice 914.1 through 914.s of the three-dimensional media plane. In some embodiments, the vertical distance between adjacent slices of the slices 914.1 through 914.s is substantially the same from the top of the three-dimensional media plane to the bottom of the three-dimensional media plane. However, the radial distance between adjacent pixels in the same slice of the slices 914.1 through 914.s gradually increases from the top of the three-dimensional media plane to the bottom of the three-dimensional media plane. Thus, in some embodiments, the two-dimensional area of the sampling kernel space 912.1 through 912.r increases from the top (or crown) of the three-dimensional media plane toward the bottom (or pop-up) of the three-dimensional media plane. In these embodiments, the two-dimensional area of the sampling kernel space 912.1 through 912.r has a minimum area at the top of the three-dimensional media plane and a maximum area at the bottom of the three-dimensional media plane. For example, the horizontal distance of the sampling kernel space 912.1 through 912.r increases from the top of the three-dimensional media plane toward the bottom of the three-dimensional media plane, while the vertical distance of the sampling kernel space 912.1 through 912.r remains about the same.

[0082] In identifying the pixels 906.1 through 906.m within the sampling kernel space 912.1 through 912.r, the kernel-based sampling technique 900 can weight the color information (e.g., luminance and / or chrominance components of a YUV color model, and red, green, and / or blue components of an RGB color model) of these pixels in substantially the same manner as the kernel-based sampling technique 800 described above in FIG. 8 In identifying the pixels 906.1 through 906.m within the sampling kernel space 912.1 through 912.r, the kernel-based sampling technique 900 can weight the color information (e.g., luminance and / or chrominance components of a YUV color model, and red, green, and / or blue components of an RGB color model) of these pixels in substantially the same manner as the kernel-based sampling technique 800 described above in FIG. 8

[0083] Exemplary computer system that can be implemented within an exemplary image capture system and / or exemplary image projection system FIG. 10

[0084] FIG. 10 FIG. 10 illustrates a simplified block diagram of an exemplary computer system that can be implemented within an exemplary image capture system and / or an exemplary image projection system in accordance with some example embodiments of the present disclosure. The discussion that follows of FIG. 2A is intended to describe a computer system 1000 that can be implemented within the exemplary image capture system described above in FIG. 6 and / or the exemplary image projection system described above in FIG. 10 .

[0085] In FIG. 10 ​In the example embodiment shown in FIG. 10, computer system 1000 includes one or more processors 1002. In some embodiments, one or more processors 1002 can include or can be any of a microprocessor, a graphics processing unit, or a digital signal processor, and their electronic processing equivalents, such as an application-specific integrated circuit (“ASIC”) or a field-programmable gate array (“FPGA”). As used herein, the term “processor” means a tangible data and information processing apparatus that typically uses sequential transformation (also known as “operations”) on data and information. Data and information can be physically represented by electrical, magnetic, optical, or acoustic signals capable of being stored, accessed, transferred, combined, compared, or otherwise manipulated by the processor. The term “processor” can represent a single processor and multi-core systems or multi-processor arrays, including graphics processing units, digital signal processors, digital processors, or combinations of these elements. A processor can be electronic, for example, including digital logic circuitry (e.g., binary logic), or can be analog (e.g., operational amplifiers). A processor can also operate to support the relevant operations in a “cloud computing” environment or as a “Software as a Service” (SaaS). For example, at least some of the operations can be performed by a set of processors available in a distributed or remote system, accessible via a communication network (e.g., the Internet) and via one or more software interfaces (e.g., application program interfaces (APIs)). In some embodiments, computer system 1000 can include an operating system, such as Microsoft’s Windows, Sun Microsystems’ Solaris, Apple Computer’s MacOS, Linux, or UNIX. In some embodiments, computer system 1000 can also include a basic input / output system (BIOS) and processor firmware. The operating system, BIOS, and firmware are used by one or more processors 1002 to control the subsystems and interfaces coupled to one or more processors 1002. In some embodiments, one or more processors 1002 can include Intel’s Pentium and Itanium, Advanced Micro Devices’ Opteron and Athlon, and ARM Holdings’ ARM processors.

[0086] As FIG. 10As shown in FIG. 10, computer system 1000 can include a machine-readable medium 1004. In some embodiments, the machine-readable medium 1004 can also include a main memory 1006, a static memory 1008, and / or a file storage subsystem 1010. The main memory 1006 can store instructions and data during program execution. The static memory 1008 can store instructions and data that are not presently being used by the CPU 1002. The file storage subsystem 1010 provides persistent (non-volatile) storage for program and data files, and can include a hard disk drive, a floppy disk drive with associated removable media, a CD-ROM drive, an optical drive, or removable media cartridges. The file storage subsystem 1010 generally provides data files and data structures stored as computer-readable media 1004.

[0087] Computer system 1000 can also include a user interface input device 1012 and a user interface output device 1014. For example, user interface input device 1012 can include a keyboard, a number keypad, a mouse, a trackball, a touchpad, a stylus, a microphone, a camera, and / or other types of input devices. User interface input device 1012 can be connected to computer system 1000 by wired or wireless connections. Generally, user interface input device 1012 is designed to allow a user to identify a desired location on a user interface output device (e.g., a display subsystem) and to input information to the computer system 1000. User interface input device 1012 can include a number of devices including a touch screen that also serves as a user interface output device 1014. User interface output device 1014 can include a display subsystem, a printer, a fax machine, or non-visual displays such as audio output devices. The display subsystem can include a cathode ray tube (CRT), a flat-panel device such as a liquid crystal display (LCD), a projection device, or some other type of device for creating a visible image. The display subsystem can also provide non-visual display such as via audio output or haptic output (e.g., vibration) devices. Generally, user interface output device 1014 is designed to output information to a user.

[0088] The computer system 1000 can also include a network interface 1016 to provide a connection to an external network, including to a communication network 1018, and to corresponding interface devices in other computer systems or machines via the communication network 1018. The communication network 1018 can include many interconnected computer systems, machines, and communication links. These communication links can be wireline links, optical links, wireless links, or any other techniques for communicating information. The communication network 1018 can be any suitable network, such as a wide-area network (such as the Internet) and / or a local-area network (such as an Ethernet network). The communication network 1018 can be wired and / or wireless, and the communication network can use encryption and decryption methods, such as those provided by virtual private networks. The communication network uses one or more communication interfaces, which can receive data from and transmit data to other systems. Embodiments of communication interfaces typically include an Ethernet card, a modem (e.g., telephone, satellite, cable or ISDN), a (analog) digital subscriber line (DSL) unit, a FireWire interface, a USB interface, and the like. One or more communication protocols can be used, such as HTTP, TCP / IP, RTP / RTSP, IPX, and / or UDP.

[0089] As shown in ​ The one or more processors 1002, the machine-readable medium 1004, the user interface input devices 1012, the user interface output devices 1014, and / or the network interface 1016 can be communicatively coupled to each other using a bus subsystem 1020. While the bus subsystem 1020 is illustrated as a single bus, alternative embodiments can use multiple buses. For example, a RAM-based primary memory can communicate directly with a file storage system using a direct memory access ("DMA") system.

[0090] CONCLUSION

[0091] DETAILED DESCRIPTION The exemplary embodiments consistent with the present disclosure are illustrated by reference to the drawings. References within the present disclosure to "exemplary embodiments" indicate that the description can include, but does not necessarily include, a particular feature, structure, or characteristic. However, each

[0092] The DETAILED DESCRIPTION is not meant to be limiting. Rather, the scope of the present disclosure is defined by the appended claims and their equivalents. It is recognized that the DETAILED DESCRIPTION section, and not the SUMMARY section, is intended to be used to interpret the claims. The SUMMARY section can set forth one or more example embodiments of the present disclosure, but not all example embodiments, and thus is not intended to limit the present disclosure and the appended claims in any way.

[0093] The example embodiments described in this disclosure are provided for illustrative purposes, and are not intended to be limiting. Other example embodiments are possible, and modifications to the example embodiments can be made while remaining within the spirit and scope of the disclosure. The present disclosure has been described with the aid of functional building blocks illustrating the implementation of specified functions and relationships of the parts. Boundaries between the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternate boundaries can be defined as long as the specified functions and relationships of the parts are appropriately performed.

[0094] Embodiments of the present disclosure can be implemented in hardware, firmware, software, or any combination thereof. Embodiments of the present disclosure can also be implemented as instructions stored on a machine-readable medium, which can be read and executed by one or more processors. A machine-readable medium can include any mechanism for storing or transmitting information in a form readable by a machine (e.g., computing circuitry). For example, a machine-readable medium can include read only memory (ROM); random access memory (RAM); magnetic disk storage media; optical storage media; flash memory devices; and others. As another example, a machine-readable medium can include a transitory medium, such as electrical, optical, acoustical, or other form of propagated signals (e.g., carrier waves, infrared signals, digital signals, etc.). Further, firmware, software, routines, instructions can be described herein as performing certain actions. However, it should be appreciated that such descriptions are merely for convenience and that such actions in fact result from computing devices, processors, controllers, or other devices executing the firmware, software, routines, instructions, etc.

[0095] The DETAILED DESCRIPTION of the exemplary embodiments sufficiently reveals the general nature of the disclosure that others can modify and / or adapt various applications of the exemplary embodiments without undue experimentation to ascertain if they fall within the spirit and scope of the disclosure. Accordingly, while the specific embodiments have been illustrated and described, such is understood to be illustrative of the principles of the present disclosure only and not limiting thereof. It is therefore intended to be covered within the scope of the present disclosure and its equivalents any such adaptations or modifications as are within the spirit and scope of the present disclosure. It is to be understood that the phraseology or terminology herein is for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by those skilled in relevant art in light of the teachings and guidance.

Claims

1. An image processing server for transforming an image for projection onto a media plane of a venue, the image processor comprising: a memory configured to store instructions; as well as A processor configured to execute instructions that, when executed by the processor, configure the processor to: projecting the three-dimensional coordinates of the plurality of pixels of the media plane onto the two-dimensional coordinates of the image space of the image to provide a plurality of two-dimensional points projected onto the image, interpolating color information of the plurality of pixels of the media plane based on color information of the plurality of pixels of the image, and Color information of the plurality of pixels is provided to a venue to project an image onto a media plane. 2 . The image processing server of claim 1 , wherein the instructions, when executed by the processor, further configure the processor to reconstruct the image from one or more digital image signals associated with the image. 3 . The image processing server of claim 1 , wherein the color information of the plurality of pixels includes luminance and chrominance components of a YUV color model or red, green, and blue components of an RGB color model.

4. The image processing server of claim 1 , wherein the instructions, when executed by the processor, configure the processor to interpolate color information of pixels of a media plane among the plurality of pixels of the media plane by weighting and accumulating color information of the plurality of pixels of the image located in a sample kernel space among a plurality of sample kernel spaces of the image. 5 . The image processing server of claim 4 , wherein the instructions, when executed by the processor, configure the processor to weight the color information of the plurality of pixels of the image located in the sample kernel space according to a probability density function.

6. The image processing server according to claim 4, wherein the plurality of sample kernel spaces include a first sample kernel space having a smaller two-dimensional area than a second sample kernel space, and When executed by a processor, the instructions configure the processor to weight color information of the plurality of pixels of the image located in a first sample kernel space when the pixel of the media plane is closer to the top of the media plane, or to weight color information of the plurality of pixels of the image located in a second sample kernel space when the pixel of the media plane is closer to the bottom of the media plane.

7. The image processing server of claim 6, wherein the first sample kernel space comprises a circle, and The second sample kernel space is related to the Rosenbrock function.

8. A method for transforming an image for projection onto a media surface at a venue, the method comprising: Projecting, by a computer system, the three-dimensional coordinates of the plurality of pixels of the media plane onto the two-dimensional coordinates of the image space of the image to provide a plurality of two-dimensional points projected onto the image; interpolating, by a computer system, color information of the plurality of pixels of the media plane based on color information of the plurality of pixels of the image; as well as Color information of the plurality of pixels is provided to the venue by the computer system to project an image onto the media plane.

9. The method of claim 8, further comprising reconstructing, by a computer system, the image from one or more digital image signals associated with the image.

10. The method of claim 8, wherein the color information of the plurality of pixels comprises luminance and chrominance components of a YUV color model or red, green, and blue components of an RGB color model.

11. The method of claim 8, wherein the interpolation comprises interpolating color information of pixels of a media plane among the plurality of pixels of the media plane by weighting and accumulating color information of the plurality of pixels of the image located in a sample kernel space among a plurality of sample kernel spaces of the image. 12 . The image processing server of claim 11 , wherein interpolation further comprises weighting color information of the plurality of pixels of the image located in the sample kernel space according to a probability density function.

13. The image processing server of claim 11, wherein the plurality of sample kernel spaces include a first sample kernel space having a smaller two-dimensional area than a second sample kernel space, and The interpolation further includes weighting the color information of the multiple pixels of the image located in the first sample kernel space when the pixel of the media plane is closer to the top of the media plane, or weighting the color information of the multiple pixels of the image located in the second sample kernel space when the pixel of the media plane is closer to the bottom of the media plane.

14. The image processing server of claim 13, wherein the first sample kernel space comprises a circle, and The second sample kernel space is related to the Rosenbrock function.

15. An image processing system for transforming an image for projection onto a media plane in a venue, the image processing system an image recording system configured to store one or more digital image signals associated with the image; and The image processing server is configured as follows: reconstructing an image from the one or more digital image signals, projecting the three-dimensional coordinates of the plurality of pixels of the media plane onto the two-dimensional coordinates of the image space of the image to provide a plurality of two-dimensional points projected onto the image, interpolating color information of the plurality of pixels of the media plane based on color information of the plurality of pixels of the image, and Color information of the plurality of pixels is provided to a venue to project an image onto a media plane. 16 . The image processing system of claim 15 , wherein the color information of the plurality of pixels comprises luminance and chrominance components of a YUV color model or red, green, and blue components of an RGB color model.

17. The image processing system of claim 15 , wherein the image processing server is configured to interpolate color information of pixels of a media plane among the multiple pixels of the media plane by weighting and accumulating color information of the multiple pixels of the image within a sample kernel space among a plurality of sample kernel spaces of the image. 18 . The image processing system of claim 17 , wherein the image processing server is configured to weight the color information of the plurality of pixels of the image located in the sample kernel space according to a probability density function.

19. The image processing system of claim 17, wherein the plurality of sample kernel spaces include a first sample kernel space having a smaller two-dimensional area than a second sample kernel space, and The image processing server is configured to weight the color information of the multiple pixels of the image located in the first sample kernel space when the pixels of the media plane are closer to the top of the media plane, or to weight the color information of the multiple pixels of the image located in the second sample kernel space when the pixels of the media plane are closer to the bottom of the media plane.

20. The image processing system of claim 19, wherein the first sample kernel space comprises a circle, and The second sample kernel space is related to the Rosenbrock function.

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