Image capture for spherical venues

Abstract

The systems, methods, and apparatuses disclosed herein may include an exemplary image capture system for capturing light associated with an image within its field of view and / or an exemplary image projection system for transforming the image for projection onto a three-dimensional media surface of a three-dimensional venue. The exemplary image capture system may direct light rays captured by the exemplary image capture system onto an image sensor associated with the exemplary image capture system. As described in further detail below, the exemplary image capture system may focus these light rays toward the periphery, i.e., edge, of the image sensor. As a result, the three-dimensional venue may display the highest optical quality for the image toward the bottom, i.e., origin, of the three-dimensional media surface.

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims priority to U.S. Patent Application No. 18 / 332,855, filed June 12, 2023, and U.S. Patent Application No. 18 / 332,874, filed June 12, 2023, each of which is incorporated herein by reference in its entirety, and claims the benefit of U.S. Provisional Patent Application No. 63 / 434,309, filed December 21, 2022. [Background technology]

[0002] Content creators often use conventional ultra-wide-angle lenses, such as conventional fisheye lenses, to capture conventional images displayed by conventional three-dimensional media surfaces. A conventional fisheye lens represents one type of ultra-wide-angle lens that produces strong visual distortion, e.g., a convex, non-rectilinear appearance, and is intended to create one or more hemispherical images for display by the conventional three-dimensional media surface. Often, the center of a conventional fisheye lens can be associated with a conventional primary viewing section located at the top, i.e., apex, of the conventional three-dimensional media surface. Typically, the conventional primary viewing section can be characterized as having the highest optical image quality, e.g., resolution, compared to other viewing sections of the conventional three-dimensional media surface. The optical quality of one or more images captured by a conventional fisheye lens presented on a conventional three-dimensional media surface decreases from the conventional primary viewing section toward the bottom, i.e., origin, of the conventional three-dimensional media surface, with the lowest optical image quality occurring at the bottom of the conventional three-dimensional media surface.

[0003] Content creators often capture traditional images displayed by traditional three-dimensional media surfaces during an event. Typically, the event can be characterized as including one or more performers positioned toward the bottom of the traditional three-dimensional media surface. Often, the traditional three-dimensional media surface can display images as the one or more performers perform. Thus, an audience experiencing the event in a traditional venue typically focuses their field of view on the one or more performers toward the bottom of the traditional three-dimensional media surface. As a result, the audience will view the images on the traditional three-dimensional media surface at their lowest optical quality. To experience the images at their highest optical quality, the audience will be required to shift their field of view toward the traditional primary viewing section at the top of the traditional three-dimensional media surface, i.e., look up, which will cause the one or more performers to no longer be in their field of view. Summary of the Invention [Means for solving the problem]

[0004] (overview)

[0005] The systems, methods, and devices disclosed herein may include an exemplary image capture system for capturing light associated with one or more images within its field of view and / or an exemplary image projection system for transforming one or more images for projection onto a three-dimensional media surface of a three-dimensional venue. The exemplary image capture system may direct light rays captured by the exemplary image capture system onto an image sensor associated with the exemplary image capture system. As described in further detail below, the exemplary image capture system may focus these light rays toward the periphery, i.e., edge, of the image sensor. As a result, the three-dimensional venue may display the highest optical quality for one or more images toward the bottom, i.e., origin, of the three-dimensional media surface. Furthermore, the exemplary image capture system may be specifically fabricated to disperse the light rays captured by the exemplary image capture system heterogeneously, e.g., non-uniformly, onto the image sensor to further enhance the highest optical quality for one or more images. As described in further detail below, the exemplary image projection system may project one or more images onto a three-dimensional media surface of a three-dimensional venue. As part of this projection, the exemplary image projection system can mathematically transform two-dimensional coordinates of pixels of one or more images into three-dimensional coordinates on the three-dimensional media surface and project the one or more images onto the three-dimensional media surface. Also, as part of this projection, the exemplary image projection system can statistically interpolate color information from the one or more images to be projected onto the three-dimensional media surface. [Brief explanation of the drawings]

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

[0007] [Figure 1A] 1A and 1B illustrate a graphical representation of an example venue, according to some example embodiments of the present disclosure. [Figure 1B]1A and 1B illustrate a graphical representation of an example venue, according to some example embodiments of the present disclosure.

[0008] [Figure 2A] FIG. 2A illustrates a simplified block diagram of an exemplary image capture system, according to some exemplary embodiments of the present disclosure.

[0009] [Figure 2B] FIG. 2B illustrates a flowchart of an example operation of an example camera system that may be implemented in an example image capture system, according to some example embodiments of the present disclosure.

[0010] [Figure 3A] 3A and 3B illustrate simplified block diagrams of an example camera lens system that may be implemented in an example camera system according to some example embodiments of the present disclosure. [Figure 3B] 3A and 3B illustrate simplified block diagrams of an example camera lens system that may be implemented in an example camera system according to some example embodiments of the present disclosure.

[0011] [Figure 4] 4A and 4B illustrate simplified block diagrams of an example camera lens housing that may be implemented in an example camera system, according to some example embodiments of the present disclosure.

[0012] [Figure 5] 5A and 5B illustrate simplified block diagrams of an example camera system, according to some example embodiments of the present disclosure.

[0013] [Figure 6] FIG. 6 illustrates a simplified block diagram of an exemplary image projection system, according to some exemplary embodiments of the present disclosure.

[0014] [Figure 7] FIG. 7 illustrates a flowchart of an example kernel-based sampling technique that may be implemented in an example projection system, according to some example embodiments of the present disclosure.

[0015] [Figure 8] 8 and 9 illustrate example kernel-based sampling techniques that may be implemented within example image projection systems, according to some example embodiments of the present disclosure. [Figure 9] 8 and 9 illustrate example kernel-based sampling techniques that may be implemented within example image projection systems, according to some example embodiments of the present disclosure.

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

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

[0018] Detailed Description 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 simplify the disclosure. These, of course, are examples only and are not intended to be limiting. Aspects of the disclosure are best understood from the following detailed description when read in conjunction with the accompanying figures. The disclosure may repeat reference numerals and / or letters in the various examples. This repetition does not, in itself, dictate a relationship between the various embodiments and / or configurations discussed. Note that, in accordance with standard practice in the industry, features have not been drawn to scale. In fact, dimensions of features may be arbitrarily increased or decreased for clarity of discussion.

[0019] (Projecting Images onto an Exemplary Venues of the Present Disclosure)

[0020] 1A and 1B illustrate graphical representations of an exemplary venue according to some exemplary embodiments of the present disclosure. In the exemplary embodiment illustrated in FIGS. 1A and 1B, venue 100 represents a location for hosting an event. For example, venue 100 can represent a music venue, e.g., a music theater, music club, and / or concert hall; a sports venue, e.g., an arena, convention center, and / or stadium; and / or any other suitable venue that would be apparent to one skilled 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 sporting event, a video, and / or any other suitable event that would be apparent to one skilled in the art without departing from the spirit and scope of the present disclosure. In the exemplary embodiment illustrated in FIGS. 1A and 1B, venue 100 can represent a three-dimensional structure for hosting an event, e.g., a hemispherical structure, also referred to as a hemispherical dome. In some embodiments, venue 100 can include a three-dimensional media surface 102 for displaying one or more images associated with the event that are diffused across the interior, i.e., inner surface, of venue 100. In some embodiments, three-dimensional media surface 102 can include a series of rows and a series of columns of photographic 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, to name a few. For example, three-dimensional media surface 102 can include an approximately 16,000 x 16,000 resolution three-dimensional media surface in three-dimensional space that wraps around the interior of venue 100 and creates a visual display of approximately 160,000 square feet.

[0021] In some embodiments, the venue 100 can project one or more images onto the three-dimensional media surface 102. In these embodiments, one or more images can be projected onto the three-dimensional media surface 102 during an event to enhance the audience's visual experience when viewing the event. As illustrated in FIG. 1A , the three-dimensional media surface 102 can include a primary audience viewing section 104 having the highest optical image quality located along the interior, i.e., inner, surface of the three-dimensional media surface 102. In some embodiments, the primary audience viewing section 104 can be located approximately on a haunch approximately halfway between the top and base of the three-dimensional media surface 102, with the approximate center of the primary audience viewing section 104 indicated in a spherical coordinate system as (R, A, Θ). The primary audience viewing section 104 can be characterized as having the highest optical image quality, e.g., resolution, compared to other viewing sections of the three-dimensional media surface 102. In some embodiments, the optical quality of one or more images projected onto the three-dimensional media surface 102 decreases from the highest optical quality in the primary audience viewing section 104 along the interior of the three-dimensional media surface 102 toward another viewing section diametrically opposite the primary audience viewing section 104. As described in more detail below, an exemplary image capture system can be utilized to capture one or more images having the highest optical quality when projected onto the three-dimensional media surface 102 that are located within the primary audience viewing section 104. Also, as described in more detail below, an exemplary image projection system can be utilized to convert the two-dimensional coordinates of one or more images into three-dimensional coordinates of the three-dimensional media surface, enabling the one or more images to be projected onto the three-dimensional media surface.

[0022] In some embodiments, the center of the conventional primary viewing section 112 as described above can be represented in a spherical coordinate system as (r, α, θ). In these embodiments, the distance D between the center of the audience primary viewing section 104 and the center of the conventional primary viewing section 112 is R can be shown as follows: [ka] Also, the difference D between the polar angles between the centers of the audience primary viewing section 104 and the conventional primary viewing section θ can be shown as follows: [ka] In some embodiments, the center of the conventional primary viewing section 112 is the difference D θ can be considered to be offset from the center of the audience primary viewing section 104 by a difference D θ can be between about 30 degrees and about 90 degrees. In this embodiment, the audience primary viewing section 104 can be considered to be offset from the conventional primary viewing section 112 by between about 30 degrees and about 90 degrees.

[0023] 1B , the venue 100 can include one or more seating sections for seating an audience member to experience the event. In some embodiments, the primary audience viewing section 104 can be specifically designated, for example, by an image capture system 200, as described in further detail below, to enable one or more audience members 106 in the audience seating within the venue 100 to view one or more images projected onto the three-dimensional media surface 102 at their highest optical quality. In some embodiments, the one or more audience members 106 can include audience members from one or more rows of seats within the venue 100 and / or one or more sections of seats within the venue 100, to name a few. Also, as illustrated in FIG. 1B , the primary audience viewing section 104 can be specifically adjusted to coincide with the field of view 108 of one or more audience members 106 as they experience the event. As an example, the field of view 108 may correspond to the field of view of an audience member in a primary seating area within the venue 100, e.g., a luxury suite. In some embodiments, one or more audience members 106 may be considered to experience the projected image or images at their highest optical quality. In some embodiments, the event may be characterized as having one or more performers positioned toward the bottom of the three-dimensional media surface 102, as described above. In these embodiments, the one or more performers may be present on a stage 110 positioned toward the bottom of the three-dimensional media surface 102. In these embodiments, the primary audience viewing section 104 may be positioned behind the one or more performers, allowing the one or more audience members 106 to simultaneously view the one or more performers and the one or more images at their highest optical quality. In other words, the primary audience viewing section 104 can be positioned within the field of view 108 of one or more audience members 106 as they view one or more performers.

[0024] Exemplary Image Capture System for Capturing Images

[0025] FIG. 2A illustrates a simplified block diagram of an exemplary image capture system according to some exemplary embodiments of the present disclosure. In the exemplary embodiment illustrated in FIG. 2A, image capture system 200 captures light associated with one or more images that may be projected onto a three-dimensional media surface of a venue, such as three-dimensional media surface 102 of venue 100 as described in FIGS. 1A and 1B above. As described in further detail below, image capture system 200 can be utilized to capture one or more images having the highest optical quality that, when projected onto the three-dimensional media surface, are located within a primary audience viewing section of the three-dimensional media surface, such as primary audience viewing section 104 as described in FIGS. 1A and 1B above. As described in further detail below, image capture system 200 can direct light rays captured by image capture system 200 onto an image sensor associated with image capture system 200. As described in further detail below, image capture system 200 can focus these light rays toward the periphery, i.e., edge, of the image sensor. As a result, the three-dimensional venue can display the highest optical quality for one or more images that have the highest optical quality located within the audience's primary viewing section of the three-dimensional medium. Additionally, image capture system 200 can be specifically fabricated to disperse light captured by the exemplary image capture system heterogeneously, e.g., non-uniformly, onto the image sensor to further enhance the highest optical quality for one or more images. As illustrated in FIG. 2A , image capture system 200 can include a camera system 202 having a camera lens system 204 and a camera assembly 206 that can be communicatively coupled to an image recording system 208 via a communications network 210. While image capture system 200 is illustrated in FIG. 2A as including multiple discrete devices, those skilled in the art will recognize that one or more of these devices can be combined without departing from the spirit and scope of the present disclosure.For example, as would be apparent to one skilled in the art without departing from the spirit and scope of the present disclosure, camera system 202 may include camera lens system 204, camera assembly 206, and / or image recording system 208 as a single discrete device without communication network 210.

[0026] In the exemplary embodiment illustrated in FIG. 2A , camera lens system 204 projects one or more images within its field of view, e.g., light associated with a scene, onto image sensor 212 of camera assembly 206, which is described in further detail below. In some embodiments, camera lens system 204 can focus, e.g., converge, the captured light onto image sensor 212 to generate one or more images for projection onto the three-dimensional media surface of the venue. For example, camera lens system 204 can focus light reflected from one or more physical objects in the scene onto image sensor 212 to generate one or more images of the one or more physical objects for projection onto the three-dimensional media surface of the venue. In the exemplary embodiment illustrated in FIG. 2A , camera lens system 204 can include a camera lens housing and a camera lens system. In some embodiments, the camera lens housing can be implemented to form a perspective control lens, such as a shifting lens or a tilt-shifting lens, to name a few. 1A and 1B above, a perspective control lens can be utilized by image capture system 200 to focus, e.g., converge, light captured by image capture system 200 onto one or more sections of image sensor 212 associated with a primary audience viewing section of the three-dimensional media surface. In some embodiments, the perspective control lens can change the orientation or position of the camera lens system, e.g., tilt, shift, and / or rotate it relative to camera assembly 206, to designate one or more sections of image sensor 212. For example, the perspective control lens can steer the orientation or position of the center of the camera lens system, e.g., the center of an ultra-wide-angle lens, such as a fisheye lens or a rectilinear lens, relative to image sensor 212. Generally, an ultra-wide-angle lens refers to any suitable lens having a field of view of about 100 to about 180 degrees, as would be recognized by one of ordinary skill in the art without departing from the spirit and scope of the present disclosure.In this example, the perspective control lens steers the orientation or position of the center of the camera lens system toward the periphery, e.g., edge, of the image sensor 212, causing light captured by the center of the camera lens system to focus toward the periphery, e.g., edge, of the image sensor 212. In some embodiments, the periphery, e.g., edge, of the image sensor 212 may be approximately the outermost ⅛ to ¼ of the surface area of ​​the image sensor 212. Thus, when one or more images projected near the periphery of the image sensor 212 are projected onto a three-dimensional media surface such as that described in FIGS. 1A and 1B above, the highest optical quality of the one or more images can be located along the interior of the three-dimensional media surface within the primary viewing section of the audience.

[0027] In some embodiments, the camera lens system may include a simple single lens of a transparent material. However, as would be apparent to one skilled in the art without departing from the spirit and scope of the present disclosure, more complex compound lenses of a transparent material, such as doublet lenses, triplet lenses, and / or achromatic lenses, are also possible. In these embodiments, the transparent material may include glass, crystal, and / or plastic, such as acrylic, to name a few. In some embodiments, these complex compound lenses may be configured and arranged to form ultra-wide-angle lenses, such as a fisheye lens, which produces strong visual distortion intended to create one or more hemispherical images, and / or a rectilinear lens with little or no barrel or pincushion distortion, resulting in one or more images in which linear features, such as the edges of building walls, appear straight, as opposed to curved, as in a fisheye lens. In some embodiments, the ultra-wide-angle lenses may be specifically manufactured to direct light captured by the camera lens system in a heterogeneous, e.g., non-uniform, manner so that it is distributed on the image sensor 212 around 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, as compared to a conventional ultra-wide-angle lens as described above, which projects light uniformly. For example, the camera lens system may focus light onto the image sensor 212 such that it is more concentrated near the center of the image sensor 212 as compared to the periphery of the image sensor 212. In some embodiments, the camera lens system may focus light near the center of the image sensor 212, projecting more detail about one or more images, e.g., 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 disperses light captured by the perspective control lens heterogeneously, the image or images projected within the primary audience viewing section include even more detail, and therefore even higher resolution, within the primary audience viewing section compared to implementing the camera lens system 204 with only the perspective control lens.

[0028] The camera assembly 206 captures light focused by the camera lens system 204 onto the image sensor 212 and provides one or more digital image signals, also referred to as raw image data, associated with one or more images. In some embodiments, the camera assembly 206 can reconstruct one or more images from the one or more digital image signals. In the exemplary embodiment illustrated in FIG. 2A , the camera assembly 206 can include an image sensor 212 and a processor 214. Generally, the image sensor 212 converts light, i.e., photons, focused onto the image sensor 212 by the camera lens system 204 into electrical signals. In some embodiments, the image sensor 212 can convert the electrical signals from a representation in the analog signal domain to a representation in the digital signal domain and provide one or more digital image signals that are stored by the image recording system 208, as described in further detail below. In some embodiments, the image sensor 212 can include small photographic elements, also referred to as pixels, which can include photosensitive elements, microlenses, and / or microelectrical components. In some embodiments, the pixels can be organized and arranged as a series of rows and a series of columns to form an array of pixels, e.g., a square array of pixels. In these embodiments, the image sensor 212 can include 18,000 rows of pixels and 18,000 columns of pixels to form a square array of 18,000 by 18,000 pixels. In some embodiments, the image sensor 212 can be implemented as a charge-coupled device (CCD) or active pixel sensor, which can be fabricated in complementary metal-oxide-silicon (CMOS) and / or n-type metal-oxide-silicon (NMOS) technology. In these embodiments, the image sensor 212 can be implemented as, for example, a color sensor that includes a color mask, such as a Bayer mask, that absorbs undesired color wavelengths so that each pixel of the image sensor 212 is sensitive to a specific color wavelength, and / or a monochrome sensor without a color mask so that each pixel of the image sensor 212 is sensitive to all visible light wavelengths.In these embodiments, the one or more digital image signals may include color information for each pixel of the image sensor 212, e.g., the luminance and / or chrominance components of the YUV color model and / or the red, green, and / or blue color components of the RGB color model, to name a few.

[0029] The processor 214 may provide one or more digital image signals developed by the image sensor 212 to the image recording system 208. Alternatively, or additionally, the processor 214 may 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 may implement one or more digital image processing techniques, also referred to as digital photographic processing techniques, to process the one or more digital image signals developed by the image sensor 212 and reconstruct one or more images from the one or more digital image signals. In some embodiments, the one or more digital image processing techniques may include decoding, demosaicing, bad pixel removal, white balance, noise reduction, color conversion, tone reproduction, compression, systematic noise removal, dark frame subtraction, optical correction, contrast manipulation, unsharp masking, and / or any other suitable well-known digital image processing techniques that may be apparent to one skilled in the art without departing from the spirit and scope of the present disclosure. In some embodiments, processor 214 can format one or more digital image signals and / or one or more images for transmission to image recording system 208 via communications network 210. In some embodiments, processor 214 can compress one or more digital image signals and / or one or more images using, for example, a lossless compression technique, e.g., a Lempel-Ziv based lossless compression technique, and / or a lossy compression technique, e.g., a discrete cosine transform (DCT) based lossy compression technique. In some embodiments, processor 214 can include or be coupled to an electrical-to-optical converter to convert one or more digital image signals from electrical signals to optical signals for transmission via an optical fiber network.

[0030] The image recording system 208 can store one or more digital image signals and / or one or more images provided by the processor 214. As described in more detail below, the one or more digital image signals and / or one or more images can be further processed by an image projection system for projection onto a three-dimensional media surface of the venue plane in a manner substantially similar to that described in FIGS. 1A and 1B above. 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 light captured by the image capture system. These radiometric characteristics can include color information for each pixel of the image sensor, e.g., the luminance and / or chrominance components of the YUV color model and / or the red, green, and / or blue components of the RGB color model, to name a few. Alternatively, or in addition, image recording system 208 may store one or more images in any suitable, well-known image file format, such as the Joint Photographic Experts Group (JPEG) image file format, the Exchangeable Image File Format (EXIF), the Tagged Image File Format (TIFF), the Graphics Interchange Format (GIF), the Bitmap Image File (BMP) format, or the Portable Network Graphics (PNG) image file format, to name a few, as would be apparent to one of ordinary skill in the art without departing from the spirit and scope of this disclosure. In some embodiments, image recording system 208 may include a machine-readable medium to store one or more digital image signals and / or one or more images provided by processor 214 in a form readable by a machine, such as a computing device, to name a few. In these embodiments, the machine-readable medium may include read-only memory (ROM), random-access memory (RAM), magnetic disk storage media, optical storage media, flash memory devices, among others.Alternatively, or in addition, the machine-readable medium may include a hard disk drive, e.g., a solid state drive, a floppy disk drive and associated removable media, a CD-ROM drive, an optical drive, a flash memory, or a removable media cartridge, which may enable persistent storage of one or more digital image signals by the camera assembly 206.

[0031] Communications network 210 communicatively couples camera system 202 and image recording system 208. Communications network 210 can be implemented as a wireless communications network, a wired communications network, and / or any combination thereof as would be apparent to one skilled in the art without departing from the spirit and scope of the present disclosure. In some embodiments, communications network 210 can include a fiber optic network and / or a coaxial network that uses fiber optic and / or coaxial cable to deliver one or more digital image signals and / or one or more images from camera system 202 to image recording system 208. In some embodiments, communications network 210 can include a hybrid fiber coaxial (HFC) network that combines fiber optic and coaxial cable to deliver one or more digital image signals and / or one or more images from camera system 202 to image recording system 208.

[0032] Example Camera Systems That May Be Implemented Within the Example Camera System

[0033] 2B illustrates a flowchart of an example operation of an example camera system that may be implemented in an example image capture system according to some example embodiments of the present disclosure. The present disclosure is not limited to this operational description. Rather, it will be apparent to those skilled in the art 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 associated with one or more images, e.g., a scene, within its 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 camera system 202 having camera lens system 204 and camera assembly 206 as described in FIG. 2A above.

[0034] In operation 252, the motion control flow 250 can steer the center of the camera lens system toward the periphery, i.e., edge, of the image sensor of the camera assembly, directing light captured by the center of the camera lens system toward the periphery, i.e., edge, of the image sensor. In some embodiments, the motion control flow 250 can change the orientation or position of the camera lens system, e.g., tilt, shift, and / or rotate it relative to the camera assembly. For example, the motion control flow 250 can steer the orientation or position of the center of the camera lens system, e.g., the center of an ultra-wide-angle lens such as a fisheye lens or a rectilinear lens, relative to the image sensor. In this example, the motion control flow 250 can steer the orientation or position of the center of the camera lens system toward the periphery, e.g., edge, of the image sensor, focusing light captured by the center of the camera lens system toward the periphery, i.e., edge, of the image sensor. In some embodiments, the motion control flow 250 can, for example, focus light captured from one or more images toward the periphery, i.e., edge, of the image sensor.

[0035] In operation 254, operation control flow 250 can focus the light captured by the camera lens system from operation 252 so that it is distributed non-uniformly on the image sensor around the periphery of the image sensor. In some embodiments, operation control flow 250 can direct the light captured by the camera lens system from operation 252 non-uniformly, e.g., so that it is distributed non-uniformly on the image sensor around an approximate center of the image sensor. In these embodiments, the angular distribution of light from operation 252 can be characterized as non-uniform across the image sensor, compared to a conventional ultra-wide-angle lens, as described above, which projects light uniformly. For example, operation control flow 250 can focus the light from operation 252 onto the image sensor so that it is more concentrated near the center of the image sensor compared to the periphery of the image sensor. In some embodiments, operation control flow 250 can focus the light near the center of the image sensor, allowing more detail about the image, e.g., more detail of the scene, to be projected near the center of the image sensor.

[0036] Exemplary Camera Lens Systems That May Be Implemented in Exemplary Camera Systems

[0037] 3A and 3B illustrate simplified block diagrams of exemplary camera lens systems that may be implemented within exemplary camera systems according to some exemplary embodiments of the present disclosure. In the exemplary embodiment illustrated in FIG. 3A, camera lens system 302 projects light associated with one or more images, e.g., scenes, within its field of view onto image sensor 304. As described in further detail below, camera lens system 302 may direct light toward image sensor 304 to provide a heterogeneous, e.g., non-uniform, distribution of light on image sensor 304. Camera lens system 302 and image sensor 304 may represent exemplary embodiments of camera lens systems such as camera lens system 204 and image sensor 212, respectively, as described in FIG. 2A above.

[0038] The camera lens system 302 is described in further detail below in terms of exemplary ray tracing of light rays 350.1-350.n onto the image sensor 304. However, it should be noted that the exemplary ray tracing as illustrated in FIG. 3A is for illustrative purposes only. Those skilled in the art will recognize that light rays 350.1 and 350.n may differ from those illustrated in FIG. 3A without departing from the spirit and scope of the present disclosure. As illustrated in FIG. 3A, the camera lens system 302 can capture light rays 350.1-350.n within its field of view. In some embodiments, light rays 350.1-350.n may, for example, be reflected from one or more physical objects within a scene within its field of view. In the exemplary embodiment illustrated in FIG. 3A, light rays 350.1-350.n may be characterized as having different angles of incidence relative to the camera lens system 302. In some embodiments, the rays of rays 350.1-350.n closest to the periphery, i.e., edge, of the field of view of camera lens system 302, e.g., rays 350.1 and 350.n, may be characterized as having the largest angle of incidence, e.g., approximately half, of the field of view of camera lens system 302. For example, camera lens system 302 may have a field of view of 160 degrees. In this example, rays 350.1 and 350.n may be characterized as having an angle of incidence of approximately 80 degrees relative to camera lens system 302, as illustrated in FIG. 3A. In some embodiments, the central ray of rays 350.1-350.n, e.g., ray 350.5, may be characterized as having the smallest angle of incidence, e.g., approximately zero degrees. In these embodiments, the central ray may be characterized as propagating parallel to camera lens system 302.

[0039] After capturing light rays 350.1-350.n, camera lens system 302 can focus, e.g., converge, light rays 350.1-350.n using a simple single lens of transparent material. However, as would be apparent to one skilled in the art without departing from the spirit and scope of this disclosure, more complex compound lenses of transparent material, such as doublets, triplets, and / or achromatic lenses, are also possible. In these embodiments, the transparent material can include glass, crystal, and / or plastic, such as acrylic, to name a few. In some embodiments, these complex compound lenses can be configured and arranged to form ultra-wide-angle lenses, such as a fisheye lens, which produces strong visual distortion intended to create one or more hemispherical images, and / or a rectilinear lens with little or no barrel or pincushion distortion, resulting in one or more images in which linear features, such as the edges of building walls, appear straight, as opposed to curved, as in a fisheye lens.

[0040] After being focused by the camera lens system 302, the light rays 350.1-350.n may exit the camera lens system 302 and provide light rays 352.1-352.n toward the image sensor 304. In the exemplary embodiment illustrated in FIG. 3A , the camera lens system 302 may angularly distribute the light rays 352.1-352.n heterogeneously, e.g., non-uniformly, across the image sensor 304. For example, the angular distribution of the light rays 352.1-352.n may be characterized as being non-uniform across the image sensor 304 compared to conventional light rays 354.1-354.n exiting a conventional ultra-wide-angle lens, e.g., a conventional fisheye lens, as described above. In this example, the conventional light rays 354.1-354.n may be characterized as being uniformly distributed across the image sensor 304. As illustrated in FIG. 3B , conventional light rays 354.1-354.n, shown for convenience only as conventional light rays 354, can be uniformly distributed about a central ray among light rays 350.1-350.n, e.g., corresponding to ray 350.5. In some embodiments, conventional light rays 354 can be considered to be uniformly or equally spaced from one another on image sensor 304 about the central ray. Also, as illustrated in FIG. 3B , light rays 352.1-352.n, shown for convenience only as light rays 352, can be non-uniformly distributed about a central ray among light rays 350.1-350.n, e.g., corresponding to ray 350.5. In some embodiments, light rays 352.1-352.n can be considered to be non-uniformly or differently spaced from one another on image sensor 304 about the central ray. In these embodiments, the light rays 352 may be more concentrated near the center of the image sensor 304 compared to the periphery, i.e., edges, of the image sensor 304. In these embodiments, the pixels of the image sensor 304 may be distributed throughout the image sensor 304 to provide a first pixel density, e.g., 70 pixels per degree (PPD), at the center of the image sensor 304 and taper to a second pixel density, e.g., 140 pixels per degree (PPD), near the periphery of the image sensor 304.In these embodiments, the pixels of the image sensor 304 may taper linearly, e.g., uniformly, and / or non-linearly, e.g., non-uniformly, from a first pixel density to a second first pixel density.

[0041] In some embodiments, the image sensor 304 may be characterized as having a lower angular resolution at the center compared to the periphery of the image sensor 304 because the image sensor 304 captures more of the light rays 352.1-352.n near the center of the image sensor 304, as illustrated in FIGS. 3A and 3B. In these embodiments, the angular resolution relates to the minimum angular distance between objects at which the image sensor 304 assembly can discern resolvable detail. Typically, a lower angular resolution indicates that the image sensor 304 can discern more detail in one or more images, e.g., a scene, within its field of view compared to a higher angular resolution. Thus, a lower angular resolution is often associated with a higher optical image quality, e.g., magnification, than a higher angular resolution. As shown in FIG. 3B, the lowest angular resolution, and therefore the highest optical image quality, is near the center of the image sensor 304, where the concentration of light rays 352.1-352.n is greatest, and the highest angular resolution, and therefore the lowest optical image quality, is near the periphery of the image sensor 304, where the concentration of light rays 352.1-352.n is least.

[0042] Exemplary Camera Lens Housings That May Be Implemented in Exemplary Camera Systems

[0043] 4A and 4B illustrate simplified block diagrams of an exemplary camera lens housing that may be implemented within an exemplary camera system according to some exemplary embodiments of the present disclosure. In the exemplary embodiment illustrated in FIGS. 4A and 4B, a camera lens housing 402 projects light onto an image sensor 404. As described in further detail below, the camera lens housing 402 can change the orientation or position of the camera lens housing 402, e.g., tilt, shift, and / or rotate relative to the image sensor 404. Thus, the camera lens housing 402 can steer the orientation or position of the center of the camera lens housing 402 and 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 may represent exemplary embodiments of the camera lens housings of the camera lens system 204 and the image sensor 212, respectively, as described in FIG. 2A above.

[0044] In the exemplary embodiment illustrated in FIG. 4A , camera lens housing 402 can be implemented to form a perspective-control lens, such as a shifting lens or a tilt-shifting lens, to name a few. As illustrated in FIG. 4A , camera lens housing 402 can capture light rays 450 within its field of view. In some embodiments, light rays 450 can be reflected, for example, from one or more physical objects in a scene. After capturing light rays 450, camera lens housing 402 can focus, e.g., converge, light rays 450 using a simple single lens of transparent material. However, more complex compound lenses of transparent material, such as doublets, triplet lenses, and / or achromatic lenses, are also possible, as would be apparent to one skilled in the art, 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 compound lenses can be configured and arranged to form ultra-wide angle lenses, such as, to name a few, fisheye lenses that produce strong visual distortion intended to create one or more hemispherical images, and / or rectilinear lenses with little or no barrel or pincushion distortion that result in one or more images in which linear features, such as the edges of building walls, appear straight as opposed to curved in a fisheye lens.

[0045] After being focused by camera lens housing 402, light rays 450 may exit camera lens housing 402 and provide light rays 452.1 and / or light rays 452.2 toward image sensor 404. In some embodiments, camera lens housing 402 may focus light rays 450 captured from one or more images, e.g., a scene, and provide light rays 452.1 corresponding to the one or more images to image sensor 404. In some embodiments, camera lens housing 402 may focus light rays 452.1 onto the center of image sensor 404. As illustrated in FIG. 4B , the center of camera lens housing 402 may be oriented or positioned relative to image sensor 404 and configured and arranged to project center 454.1 of a simple single lens and / or compound lens of camera lens housing 402 onto the center of image sensor 404. In some embodiments, 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 surface, such as, for example, three-dimensional media surface 102, in a manner substantially similar to that described above in Figures 1A and 1B. In these embodiments, the one or more images that can be projected onto the three-dimensional media surface can be characterized as having their highest optical image quality, e.g., resolution, at the top of the three-dimensional media surface within conventional primary viewing section 112, as described above.

[0046] Alternatively or additionally, the camera lens housing 402 can, for example, focus light rays 450 captured from a scene and provide light rays 452.2 corresponding to one or more images to the image sensor 404. In some embodiments, the camera lens housing 402 can focus the light rays 452.2 toward a periphery, e.g., an edge, of the image sensor 404. In these embodiments, the camera lens housing 402 can change the orientation or position of the camera lens housing 402, e.g., tilt, shift, and / or rotate relative to the image sensor 404. For example, the camera lens housing 402 can steer the orientation or position of the center of the camera lens housing 402 relative to the image sensor 404. In this example, the camera lens housing 402 can steer the orientation or position of the center of the camera lens housing 402 to direct the light rays 452.2 toward a periphery, e.g., an edge, of the image sensor 404. As shown in FIG. 4A , the camera lens housing 402 can steer the orientation or position of the center of the camera lens housing 402 by a height H to shift the projection of light ray 452.2 onto the image sensor 404 by a height h. In some embodiments, the ratio between the height H and the height h is approximately 1 to 1. In these embodiments, the orientation or position of the center of the camera lens housing 402 can be steered relative to the image circle projected by the camera lens housing 402 in relation to the coverage of the image sensor 404. For example, if the image circle projected by the camera lens housing 402 is 10 mm larger than the height of the image sensor 404, the steering that can be achieved is 5 mm. In this example, after 5 mm, any additional steering of the orientation or position of the center of the camera lens housing 402 is often not beneficial.

[0047] As shown in FIG. 4B , the center of the camera lens housing 402 can be oriented or positioned relative to the image sensor 404 and configured and arranged to offset the center 454.2 of the simple single and / or compound lens of the camera lens housing 402 by a height h on the image sensor 404 compared to the center 454.1. In some embodiments, the light rays 452.2 projected onto the image sensor 404 can be reconstructed into one or more images that can be projected onto a three-dimensional media surface, such as, for example, three-dimensional media surface 102, in a manner substantially similar to that described in FIGS. 1A and 1B above. In these embodiments, the one or more images that can be projected onto the three-dimensional media surface can be characterized as having their highest optical quality, e.g., resolution, located along the interior of the three-dimensional media surface within the audience primary viewing section 104, as described in FIGS. 1A and 2B above. 1A and 2B above, may be characterized as being shifted along polar angle relative to the conventional primary viewing section 112, as described above. In these embodiments, the angular difference, i.e., shift, between the conventional primary viewing section 112 and the primary audience viewing section 104 along polar angle may be expressed as follows: [ka] In the formula, shift θ represents the angular difference, i.e., shift, between the conventional primary viewing section 112 and the audience primary viewing section 104 along the polar angle θ, height h represents the height h in millimeters (mm) as described above in FIGS. 4A and 4B, and l sensorrepresents 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 15 millimeter (mm) shift between the center of the camera lens housing 402 and the center of the image sensor 404 provides a 32 degree shift along the polar angle θ between the conventional primary viewing section 112 and the audience primary viewing section 104, for a 75 millimeter (mm) square image sensor, and a 160 degree field of view for the simple single lens of the camera lens housing 402 and / or the field of view of the compound lens of the camera lens housing 402.

[0048] (Exemplary Camera System)

[0049] 5A and 5B illustrate simplified block diagrams of exemplary camera systems according to some exemplary embodiments of the present disclosure. In the exemplary embodiment illustrated in FIG. 5A, camera lens system 500 can project light captured by camera lens system 500 onto image sensor 506. As illustrated in FIG. 5A, camera lens system 500 includes camera lens system 502, which can, for example, direct light captured from a scene onto image sensor 506. Camera lens system 502 can direct light toward image sensor 506 in a manner substantially similar to camera lens system 302 as described in FIGS. 3A and 3B above, providing a heterogeneous, e.g., non-uniform, distribution of light on image sensor 506. As illustrated in FIG. 5A, camera lens system 500 includes camera lens housing 504, which can 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, e.g., tilt, shift, and / or rotate relative to image sensor 506, in a manner substantially similar to camera lens housing 402 as described above in Figures 4A and 4B. Camera lens system 502 can represent an exemplary embodiment of camera lens system 302 as described above in Figures 3A and 3B, and / or camera lens housing 504 can represent an exemplary embodiment of camera lens housing 402 as described above in Figures 4A and 4B.

[0050] As illustrated in Figure 5A, camera lens system 502 can capture light rays 550 within its field of view in a manner substantially similar to camera lens system 302 as described above in Figures 3A and 3B. After being focused by camera lens system 502, light rays 550 can exit camera lens system 502 and provide light rays 552.1 toward image sensor 506. In the exemplary embodiment illustrated in Figure 5A, camera lens system 502 can angularly distribute light rays 552.1 heterogeneously, e.g., non-uniformly, across image sensor 506 in a manner substantially similar to camera lens system 302 as described above in Figures 3A and 3B. Also, as illustrated in Figure 5B, the center of camera lens housing 504 can be oriented or positioned relative to image sensor 506 in a manner substantially similar to that described in Figures 4A and 4B above, and can be configured and arranged to project center 554.1 of camera lens system 502 onto the center of image sensor 506. As further illustrated in Figure 5B, camera lens system 502 can angularly distribute light rays 552.1 in a heterogeneous, e.g., non-uniform, manner about the center of image sensor 506 in a manner substantially similar to camera lens system 302 as described in Figures 3A and 3B above.

[0051] Alternatively, or additionally, camera lens housing 504 can, for example, focus light rays 550 captured from a scene and provide light rays 552.2 corresponding to one or more images to image sensor 506. In the exemplary embodiment illustrated in FIG. 5A , camera lens housing 504 can change the orientation or position of camera lens system 502, e.g., tilt, shift, and / or rotate relative to image sensor 506, in a manner substantially similar to camera lens housing 402 as described in FIGS. 4A and 4B above. For example, camera lens housing 504 can steer the orientation or position of the center of camera lens system 502 relative to image sensor 506. In this example, camera lens housing 504 can steer the orientation or position of the center of camera lens system 502 to direct light rays 452.2 toward the periphery, e.g., edge, of image sensor 506, in a manner substantially similar to that described in FIGS. 4A and 4B above. As illustrated in Figure 4B, the center of camera lens housing 504 can be oriented or positioned relative to image sensor 506 in a manner substantially similar to camera lens system 402 as described in Figures 4A and 4B above, and can be configured and arranged to offset center 554.2 of camera lens system 502 by height h on image sensor 506 compared to center 554.1. As further illustrated in Figure 5B, camera lens system 502 can be specifically fabricated to direct light rays 552.2 to be heterogeneous, e.g., non-uniformly distributed on image sensor 506 around the periphery of image sensor 506. In some embodiments, camera lens system 502 can angularly distribute light rays 552.2 heterogeneously, e.g., non-uniformly, toward the periphery of image sensor 506 in a manner substantially similar to that described in Figures 3A and 3B above. For example, camera lens system 502 may focus light rays 552.2 onto image sensor 506 such that the light rays 552.2 are more concentrated near the periphery of image sensor 502 compared to the center of image sensor 506.In some embodiments, the camera lens system 502 can concentrate light near the periphery of the image sensor 502 to project more detail, e.g., more detail of a scene, for one or more images near the periphery of the image sensor 502. In these embodiments, the camera lens system 502 can concentrate light to have a first pixel density, e.g., 70 pixels per degree (PPD), near the periphery of the image sensor 502 and taper to a second pixel density, e.g., 140 pixels per degree (PPD), at the center of the image sensor 506. In these embodiments, the pixels of the image sensor 506 can taper from the first pixel density to the second pixel density linearly, e.g., uniformly, and / or nonlinearly, e.g., nonuniformly.

[0052] An exemplary image projection system for projecting captured images onto an exemplary venue.

[0053] FIG. 6 illustrates a simplified block diagram of an exemplary image projection system according to some exemplary embodiments of the present disclosure. As described above, an image capture system, such as image capture system 200 as described in FIG. 2A above, can capture one or more images that can be projected onto a three-dimensional media surface of a venue, such as three-dimensional media surface 102 of venue 100 as described in FIGS. 1A and 1B above. In the exemplary embodiment illustrated in FIG. 6, image projection system 600 can convert one or more images from two-dimensional to three-dimensional for projection onto the three-dimensional media surface. As described in further detail below, image projection system 600 can utilize kernel-based sampling techniques to project one or more photographic elements, also referred to as pixels, of the three-dimensional media surface onto one or more corresponding two-dimensional points on one or more images. In these embodiments, the kernel-based sampling technique then weights and accumulates color information of one or more pixels from one or more images in the neighborhood of one or more corresponding two-dimensional points on the one or more images, and can interpolate color information of a pixel of a three-dimensional media surface, e.g., the luminance and / or chrominance components of a YUV color model and / or the red, green, and / or blue components of an RGB color model, to name a few. As illustrated in FIG. 6 , image projection system 600 can include image recording system 208, which can be communicatively coupled to image processing server 604 and venue 606 via communications network 608. While image projection system 600 is illustrated in FIG. 6 as including multiple discrete devices, those skilled in the art will recognize that one or more of these devices can be combined without departing from the spirit and scope of the present disclosure. For example, as would be apparent to one skilled in the art, image recording system 208 and image processing server 604 can be combined into a single discrete device without communications network 608, without departing from the spirit and scope of the present disclosure.

[0054] As described above, 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 image capture system 200 as described in Figure 2A above. As described in further detail in Figure 6 below, the one or more digital image signals and / or one or more images can be further processed by image processing server 604 for projection onto a three-dimensional media surface, such as, for example, a three-dimensional media surface of venue 606, in a manner substantially similar to that described in Figures 1A and 1B above.

[0055] Image processing server 604 includes one or more computer systems for retrieving one or more images stored in image recording system 208, exemplary embodiments of which are described in further detail below. Alternatively, or additionally, image processing server 604 can reconstruct one or more images from one or more digital image signals stored in image recording system 208. In some embodiments, image processing server 604 implements one or more digital image processing techniques, also referred to as digital photographic processing techniques, to process one or more digital image signals stored in image recording system 208 and 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, bad pixel removal, white balance, noise reduction, color conversion, tone reproduction, compression, systematic noise removal, dark frame subtraction, optical correction, contrast manipulation, unsharp masking, and / or any other suitable well-known digital image processing techniques that may be apparent to one skilled in the art without departing from the spirit and scope of the present disclosure.

[0056] 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 the two-dimensional coordinates of the one or more images into three-dimensional coordinates of the venue 606, as described in further detail below, to enable the one or more images to be projected onto the venue 606. In the exemplary embodiment illustrated in FIG. 6, the image processing server 604 can utilize a kernel-based sampling technique to mathematically transform the two-dimensional coordinates of the one or more images into three-dimensional coordinates of the venue 606. In some embodiments, the kernel-based sampling technique projects the three-dimensional coordinates of pixels of the venue 606 onto the two-dimensional image space of the one or more images, effectively transforming 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 transform the three-dimensional coordinates of the venue 606 onto the two-dimensional image space of the one or more images. This transformation can spatially orient the three-dimensional coordinates of the venue 606 using the two-dimensional image space of the one or more images. For example, a kernel-based sampling technique may spatially orient the top side of the venue 606 using the top side of the two-dimensional image space of one or more images.

[0057] After mathematically transforming the two-dimensional coordinates of the one or more images, the kernel-based sampling technique statistically interpolates color information of pixels of venue 606, e.g., the luminance and / or chrominance components of a YUV color model and / or the red, green, and / or blue components of an RGB color model, to name a few, from the one or more images. In some embodiments, the kernel-based sampling technique can statistically interpolate color information of pixels of venue 606 based on color information of pixels of one or more images. In these embodiments, the kernel-based sampling technique can statistically interpolate color information of pixels of venue 606 by weighting and accumulating color information of pixels of one or more images in the neighborhood of a two-dimensional point projected onto the one or more images.

[0058] After interpolating the color information for the pixels of the venue 606, the image processing server 604 can provide the color information to the venue 606 and project an image onto the venue 606. In some embodiments, the image processing server 604 can generate quadruples for the pixels of the venue 606, including the three-dimensional coordinates of the pixels of the venue 606 and color information for the pixels of the venue 606 that has been statistically interpolated from one or more images. In the exemplary embodiment illustrated in FIG. 6, the venue 606 can represent a three-dimensional structure, for example, a hemispherical structure, also referred to as a hemispherical dome. In some embodiments, the hemispherical structure can include one or more visual displays, often referred to as a three-dimensional media surface, that are diffused within, i.e., across the interior surface of, the hemispherical structure. In these embodiments, the one or more visual displays can include a series of rows and a series of columns of photographic elements, also referred to as pixels, that form the three-dimensional media surface. 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, to name a few. For example, the three-dimensional media surface may include a 19,000 x 13,500 LED visual display that wraps around the interior of the three-dimensional structure, creating an approximately 160,000-square-foot visual display. In some embodiments, the venue 600 may illuminate the pixels of the venue 606 according to color information, for example, to project one or more images onto the three-dimensional media surface during an event. In these embodiments, one or more images may be projected onto the three-dimensional media surface during an event to enhance the audience's visual experience when viewing the event. In the exemplary embodiment illustrated in FIG. 7, the three-dimensional media surface may include a primary audience viewing section, such as primary audience viewing section 104 as described in FIGS. 1A and 1B above, having the highest optical image quality located within, i.e., along the interior surface of, the three-dimensional media surface.In some embodiments, the primary audience viewing section may be considered a hemispherical structure located generally midway between the top and base of the three-dimensional media surface, in a manner substantially similar to the primary audience viewing section 104 as illustrated in Figures 1A and 1B. The primary audience viewing section may be characterized as having the highest optical image quality, e.g., resolution, compared to other viewing sections of the three-dimensional media surface, in a manner substantially similar to the primary audience viewing section 104 as illustrated in Figures 1A and 1B. In some embodiments, the optical image quality of one or more images decreases from the highest optical image quality of the primary audience viewing section along the interior of the three-dimensional media surface toward another viewing section diametrically opposite the primary audience viewing section, in a manner substantially similar to the primary audience viewing section 104 as illustrated in Figures 1A and 1B.

[0059] Exemplary Kernel-Based Sampling Techniques That May Be Implemented in Exemplary Image Projection Systems

[0060] FIG. 7 illustrates a flowchart of an exemplary kernel-based sampling technique that may be implemented in an exemplary image projection system, according to some exemplary embodiments of the present disclosure. The present disclosure is not limited to this operational description. Rather, it will be apparent to those skilled in the art that other operational control flows are within the scope and spirit of the present disclosure. The following discussion is based on the two-dimensional coordinates (uv.x1, uv.y1), (uv.x2, uv.y2)...(uv.x) of pixels in an image. m ,uv.y m ) to the three-dimensional coordinates (pos.x) of the three-dimensional media plane of a three-dimensional venue, such as venue 100 as described above in FIGS. 1A and 1B and / or venue 606 as described above in FIG. 6. 1, pos.y1,pos.z1),(pos.x2,pos.y2,pos.z2)…(pos.x n ,pos.y n ,pos.z n ) is described. For convenience, two-dimensional coordinates (uv.x1, uv.y1), (uv.x2, uv.y2) ... (uv.xm ,uv.y m ) are collectively called the two-dimensional coordinates uv.x, uv.y, and the 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. The motion control flow 700 can be executed by one or more computer systems, such as, for example, the image processing server 604 as illustrated in FIG. 6 above.

[0061] In operation 702, the operation control flow 700 projects the three-dimensional coordinates pos.x, pos.y, and pos.z of the pixel of the three-dimensional media surface onto the image, and converts the three-dimensional coordinates pos.x, pos.y, and pos.z of the pixel of the three-dimensional media surface into two-dimensional coordinates (UV.x1, UV.y1), (UV.x2, UV.y2) ... (UV.x n ,UV.y n ) to the 2D 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 and UV.y.

[0062] In operation 704, operation control flow 700 statistically interpolates color information for pixels of the three-dimensional media plane from operation 702, 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, from the image, to name a few examples. In some embodiments, operation control flow 700 can statistically interpolate color information for pixels of the three-dimensional media plane from operation 702 based on color information for pixels of the image from operation 702. In these embodiments, operation control flow 700 can statistically interpolate color information for pixels of the three-dimensional media plane from operation 702 by weighting and accumulating color information for pixels of the image from operation 702 in neighborhoods of two-dimensional points projected onto the image from operation 702. In some embodiments, the weighting can be a distance-based weighting of color information for pixels of the image from operation 702 in neighborhoods of two-dimensional points projected onto the image from operation 702. For example, pixels of the image from operation 702 that are closer to the two-dimensional point projected onto the image from operation 702 are weighted more than pixels of the image from operation 702 that are farther from the two-dimensional point projected onto the image from operation 702. In some embodiments, if the distance between the two-dimensional point projected onto the image from operation 702 and neighboring pixels of the image may be considered a random variable, operation control flow 700 may weight the color information of neighboring 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-squared distribution, a continuous uniform distribution, and / or any other well-known probability density function that may be apparent to one skilled in the art without departing from the spirit and scope of the present disclosure.

[0063] In operation 706, the operation control flow 700 provides pixel color information to the venue for projection onto the venue in a manner substantially similar to that described in FIG. 6 above.

[0064] FIG. 8 illustrates an exemplary kernel-based sampling technique that may be implemented within an exemplary projection system according to some exemplary embodiments of the present disclosure. The following discussion of FIG. 8 further describes the kernel-based sampling technique as described in FIG. 6 above and / or the operational control flow 700 as described in FIG. 7 above. In the exemplary embodiment illustrated in FIG. 8, the kernel-based sampling technique 800 mathematically transforms two-dimensional coordinates of an image 802 into three-dimensional coordinates of a three-dimensional media plane of a three-dimensional venue 804. When executed by one or more computing devices, processors, controllers, or other electrical, mechanical, and / or electromechanical devices that may be apparent to those skilled in the art, the kernel-based sampling technique 800 can mathematically transform two-dimensional coordinates of pixels 806.1-806.m of the image 802 into three-dimensional coordinates of pixels 808.1-808.n of the three-dimensional media plane, as described in further detail below. In some embodiments, the kernel-based sampling technique 800 may represent an example embodiment of a kernel-based sampling technique as described above in Figure 6 and / or an example embodiment of the operational control flow 700 as described above in Figure 7. Also, the three-dimensional media surface may represent the venue 100 as described above in Figures 1A and 1B and / or an example embodiment of a three-dimensional media surface as described above in Figures 6 and / or 7.

[0065] In the exemplary embodiment illustrated in FIG. 8, a kernel-based sampling technique 800 calculates two-dimensional coordinates (uv.x1, uv.y1), (uv.x2, uv.y2)...(uv.x) of an image 802. m ,uv.y m ) to the 3D coordinates (pos.x1,pos.y 1, pos.z1), (pos.x2,pos.y2,pos.z2)…(pos.x n ,pos.y n ,pos.z n ), allowing the image 802 to be projected onto a three-dimensional media surface. For convenience, the two-dimensional coordinates (uv.x1, uv.y1), (uv.x2, uv.y2) ... (uv.xm ,uv.y m ) are collectively called the two-dimensional coordinates uv.x, uv.y, and the 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. As illustrated in Figure 8, the kernel-based sampling technique 800 projects the three-dimensional coordinates pos.x, pos.y, and pos.z of pixels 808.1-808.n of the three-dimensional media surface onto the two-dimensional space of the image 802, and converts the three-dimensional coordinates pos.x, pos.y, and pos.z of pixels 808.1-808.n into two-dimensional coordinates (UV.x1, UV.y1), (UV.x2, UV.y2) ... (UV.x) of two-dimensional points 810.1-810.n projected onto the two-dimensional space of the image 802. n ,UV.y n ) can be virtually converted into two-dimensional coordinates (UV.x1, UV.y1), (UV.x2, UV.y2) ... (UV.x n ,UV.y n ) are collectively referred to as two-dimensional coordinates UV.x, UV.y, which are projected onto the two-dimensional space of the image 802.

[0066] After projecting the three-dimensional coordinates pos.x, pos.y, and pos.z of pixels 808.1-808.n onto the three-dimensional media surface, the kernel-based sampling technique 800 statistically interpolates color information of pixels 808.1-808.n from image 802, e.g., the luminance and / or chrominance components of the YUV color model and / or the red, green, and / or blue components of the RGB color model, to name a few. In some embodiments, the kernel-based sampling technique 800 can statistically interpolate color information of pixels 808.1-808.n based on color information of pixels 806.1-806.m. In these embodiments, the kernel-based sampling technique 800 can statistically interpolate color information of pixels 808.1-808.n by weighting and accumulating color information of neighboring pixels 806.1-806.m of two-dimensional points 810.1-810.n.

[0067] 8, the kernel-based sampling technique 800 can weight color information of neighboring pixels 806.1-806.m of two-dimensional points 810.1-810.n. In some embodiments, the kernel-based sampling technique 800 can identify neighboring pixels 806.1-806.m of two-dimensional points 810.1-810.n. In these embodiments, the neighboring pixels 806.1-806.m of two-dimensional points 810.1-810.n can be placed within a region of interest (ROI), also referred to as a sampling kernel space 812.1-812.r of image 802. In general, the sampling kernel space 812.1-812.r can be any geometric region within the two-dimensional space of image 802 that includes one or more of pixels 806.1-806.m, as would be apparent to one skilled in the art, without departing from the spirit and scope of this disclosure. In some embodiments, any geometric region can include a closed geometric region, such as a regular curve, e.g., a circle or ellipse, an irregular curve, a regular polygon, e.g., an equilateral triangle or square, and / or an irregular polygon, e.g., a rectangle and / or a parallelogram, to name a few. Alternatively, or additionally, any geometric region can be associated with one or more mathematical functions, such as an A.C. Kley function, a Himmelblau function, a Rastrigin function, a Rosenbrock function (also known as Rosenbrock's banana function), and / or a Shekel function, to name a few. 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 differ from one another.For example, the kernel-based sampling technique 800 may utilize one or more mathematical functions, such as, for example, a Rosenbrock function, as the arbitrary geometric region for a first sampling kernel space among the sampling kernel spaces 812.1-812.r, and a regular curve, such as, for example, a circle, as the arbitrary geometric region for a second sampling kernel space among the sampling kernel spaces 812.1-812.r. In some embodiments, the arbitrary geometric region may be associated with three-dimensional coordinates pos.x, pos.y, and pos.z of pixels 808.1-808.n on a three-dimensional media surface. In these embodiments, the kernel-based sampling technique 800 may utilize a first arbitrary geometric region for a first sampling kernel space when the three-dimensional coordinates pos.x, pos.y, and pos.z for the corresponding pixel thereof are near the top, i.e., the apex, of the three-dimensional media surface, and / or a second arbitrary geometric region for a second sampling kernel space when the three-dimensional coordinates pos.x, pos.y, and pos.z for the corresponding pixel thereof are near the bottom, i.e., the origin, of the three-dimensional media surface.

[0068] After identifying pixels 806.1-806.m in sampling kernel space 812.1-812.r, kernel-based sampling technique 800 can weight the color information of these pixels, e.g., the luminance and / or chrominance components of the YUV color model and / or the red, green, and / or blue components of the RGB color model, to name a few. In some embodiments, the weighting can be a distance-based weighting of the color information of pixels 806.1-806.m in sampling kernel space 812.1-812.r. For example, pixels 806.1-806.m in sampling kernel space 812.1-812.r that are closer to two-dimensional points 810.1-810.n are weighted more heavily than pixels 806.1-806.m in sampling kernel space 812.1-812.r that are farther from two-dimensional points 810.1-810.n. In some embodiments, if the distance between pixels 806.1-806.m and two-dimensional points 810.1-810.n in the sampling kernel space 812.1-812.r can be considered a random variable, the kernel-based sampling technique 800 can weight the color information of pixels 806.1-806.m in 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 that may be apparent to one skilled in the art without departing from the spirit and scope of the present disclosure.

[0069] Once the color information for pixels 806.1-806.m in sampling kernel space 812.1-812.r has been weighted, the kernel-based sampling technique 800 can accumulate the weighted color information for these pixels and statistically interpolate the color information for pixels 808.1-808.n. In the exemplary embodiments illustrated in Figure 8, the kernel-based sampling technique 800 can accumulate the color information for pixels 806.1-806.m in sampling kernel space 812.1-812.r, which have been weighted as described above, and statistically interpolate the color information for two-dimensional points 810.1-810.n. In these embodiments, the kernel-based sampling technique 800 can associate two-dimensional points 810.1-810.n projected onto the two-dimensional space of the image 802 with their corresponding ones of pixels 808.1-808.n in the three-dimensional media plane. The kernel-based sampling technique 800 can then associate color information for the two-dimensional points 810.1-810.n with their corresponding ones of the pixels 808.1-808.n and statistically interpolate the color information for the pixels 808.1-808.n. In some embodiments, the kernel-based sampling technique 800 can generate quadruples for the pixels 808.1-808.n that include the three-dimensional coordinates pos.x, pos.y, and pos.z of the pixels 808.1-808.n and the information color related to the pixels 808.1-808.n that has been statistically interpolated from the image 802.

[0070] FIG. 9 illustrates an exemplary kernel-based sampling technique that may be implemented within an exemplary projection system according to some exemplary embodiments of the present disclosure. The following discussion of FIG. 9 further describes an exemplary embodiment with respect to the sampling kernel space of kernel-based sampling technique 800 as described in FIG. 8 above. In the exemplary embodiment illustrated in FIG. 9, kernel-based sampling technique 900 mathematically transforms two-dimensional coordinates of image 902 into three-dimensional coordinates of a three-dimensional media surface of a three-dimensional venue 904. When executed by one or more computing devices, processors, controllers, or other electrical, mechanical, and / or electromechanical devices that may be apparent to those skilled in the art, kernel-based sampling technique 900 can mathematically transform two-dimensional coordinates of pixels 906.1-906.m of image 902 onto three-dimensional coordinates of pixels 908.1-908.n of the three-dimensional media surface, as described in further detail below. In some embodiments, kernel-based sampling technique 900 may represent an exemplary embodiment of kernel-based sampling technique 800 as described in FIG. 8 above. Thus, kernel-based sampling technique 900, as described in further detail below, shares many substantially similar features with kernel-based sampling technique 800 as described in FIG. 8 above, and therefore only the differences between kernel-based sampling technique 800 and kernel-based sampling technique 900 are described in further detail below.

[0071] As illustrated in FIG. 9, the kernel-based sampling technique 900, in a manner substantially similar to the kernel-based sampling technique 800 as described in FIG. 8 above, can project the three-dimensional coordinates pos.x, pos.y, and pos.z of pixels 908.1-908.n of a three-dimensional media surface onto the two-dimensional space of image 902 and effectively convert the three-dimensional coordinates pos.x, pos.y, and pos.z of pixels 908.1-908.n into two-dimensional coordinates uv.x, uv.y of two-dimensional points 910.1-910.n projected onto the two-dimensional space of image 902.

[0072] After projecting the three-dimensional coordinates pos.x, pos.y, and pos.z of pixels 908.1-908.n, the kernel-based sampling technique 900 statistically interpolates color information, e.g., the luminance and / or chrominance components of the YUV color model and / or the red, green, and / or blue components of the RGB color model, to name a few, of the three-dimensional media surface from image 902 in a manner substantially similar to the kernel-based sampling technique 800 as described above in Figure 8. However, as illustrated in Figure 9, neighboring pixels 906.1-906.m of two-dimensional points 910.1-910.n can be placed within a region of interest (ROI), also referred to as the sampling kernel space 912.1-912.r of image 902. As illustrated in FIG. 9, two-dimensional point 910.1 corresponding to pixel 908.1 can be placed within sampling kernel space 912.1, two-dimensional point 910.a corresponding to pixel 908.a can be placed within sampling kernel space 912.b, and / or two-dimensional point 910.n corresponding to pixel 908.n can be placed within sampling kernel space 912.n.

[0073] In the exemplary embodiment illustrated in FIG. 9 , the two-dimensional area of ​​the sampling kernel space 912.1-912.r can be related to the distance between pixels 908.1-908.n in the three-dimensional media plane. As illustrated in FIG. 9 , the pixels 908.1-908.n can be located along circles or slices 914.1-914.s in the three-dimensional media plane. In some embodiments, the vertical distance between adjacent ones of the slices 914.1-914.s is approximately 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 one of the slices 914.1-914.s 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 912.1-912.r increases from the top, i.e., the top, of the three-dimensional media plane to the bottom, i.e., the origin, of the three-dimensional media plane. In these embodiments, the two-dimensional areas of the sampling kernel spaces 912.1-912.r are at their smallest areas at the top of the three-dimensional media surface and at their largest areas at the bottom of the three-dimensional media surface. For example, the horizontal distance of the sampling kernel spaces 912.1-912.r increases from the top of the three-dimensional media surface to the bottom of the three-dimensional media surface, while the vertical distance of the sampling kernel spaces 912.1-912.r remains approximately the same.

[0074] After identifying pixels 906.1-906.m within sampling kernel space 912.1-912.r, kernel-based sampling technique 900 may weight the color information of these pixels, e.g., the luminance and / or chrominance components of the YUV color model and / or the red, green, and / or blue components of the RGB color model, to name a few, in a manner substantially similar to kernel-based sampling technique 800 as described above in Figure 8. Additionally, once the color information of pixels 906.1-906.m within sampling kernel space 912.1-912.r has been weighted, kernel-based sampling technique 900 may accumulate the weighted color information of these pixels and statistically interpolate the color information of pixels 908.1-908.n in a manner substantially similar to kernel-based sampling technique 800 as described above in Figure 8.

[0075] Example Computer Systems That May Be Implemented Within Example Image Capture Systems and / or Example Image Projection Systems

[0076] 10 illustrates a simplified block diagram of an example computer system that may be implemented within an example image capture system and / or an example image projection system, according to some example embodiments of the present disclosure. The following discussion of FIG. 10 describes a computer system 1000 that may be implemented within an example image capture system such as that described in FIG. 2A above and / or an example image projection system such as that described in FIG. 6 above.

[0077] In the embodiment illustrated in FIG. 10 , computer system 1000 includes one or more processors 1002. In some embodiments, one or more processors 1002 can include or 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” refers to a tangible data and information processing device that typically physically transforms data and information using sequence transformations (also referred to as “operations”). Data and information can be physically represented by electrical, magnetic, optical, or acoustic signals that can be stored, accessed, transferred, combined, compared, or otherwise manipulated by the processor. The term “processor” can refer to single processors as well as multi-core systems or multi-processor arrays that include a graphics processing unit, a digital signal processor, a digital processor, or a combination of these elements. The processor can be, for example, an electronic device comprising digital logic circuitry (e.g., binary logic) or analog (e.g., operational amplifiers). The processor may also operate to support the performance of related operations within a "cloud computing" environment or as "software as a service" (SaaS). For example, at least some of the operations may be performed by a group of processors available in a distributed or remote system, which are accessible via a communications network (e.g., the Internet) and via one or more software interfaces (e.g., application program interfaces (APIs)).In some embodiments, computer system 1000 may include an operating system such as Microsoft Windows®, Sun Microsystems' Solaris®, Apple Computer's Mac OS®, Linux®, or UNIX®. In some embodiments, computer system 1000 may 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 subsystems and interfaces coupled to one or more processors 1002. In some embodiments, one or more processors 1002 may include Pentium® and Itanium processors manufactured by Intel, Opteron and Athlon processors manufactured by Advanced Micro Devices, and ARM processors manufactured by ARM Holdings.

[0078] 10, computer system 1000 can include machine-readable medium 1004. In some embodiments, machine-readable medium 1004 can further include main random access memory (“RAM”) 1006, read-only memory (“ROM”) 1008, and / or file storage subsystem 1010. RAM 1030 can store instructions and data during program execution, while ROM 1032 can store fixed instructions. File storage subsystem 1010 provides persistent storage for program and data files and may include hard disk drives, floppy disk drives and associated removable media, CD-ROM drives, optical drives, flash memory, or removable media cartridges.

[0079] The computer system 1000 may further include a user interface input device(s) 1012 and a user interface output device(s) 1014. The user interface input device(s) 1012 may include, to name a few, pointing devices such as an alphanumeric keyboard, keypad, mouse, trackball, touchpad, stylus, or graphics tablet; scanner; touchscreen integrated into a display; audio input devices such as a voice recognition system or microphone; eye gaze recognition; electroencephalogram (EEG) pattern recognition; and other types of input devices. The user interface input device(s) 1012 may be connected to the computer system 1000 by wire or wirelessly. Generally, the user interface input device(s) 1012 is intended to include all possible types of devices and methods for inputting information into the computer system 1000. The user interface input device(s) 1012 typically allow a user to identify objects, icons, text, and the like that appear on some type of user interface output device, e.g., a display subsystem. The user interface output device(s) 1020 may include a non-visual display such as a display subsystem, printer, fax machine, or audio output device. The display subsystem may include a flat panel device such as a cathode ray tube (CRT), a liquid crystal display (LCD), a projection device, or some other device for producing a visible image, such as a virtual reality system. The display subsystem may also provide a non-visual display, such as via audio output or haptic output (e.g., vibration) devices. Generally, user interface output devices 1020 are intended to include all possible types of devices and methods for outputting information from computer system 1000.

[0080] The computer system 1000 may further include a network interface 1016 for providing an interface to outside networks, including an interface to a communications network 1018, via which it is coupled to corresponding interface devices in other computer systems or machines. The communications network 1018 may comprise many interconnected computer systems, machines, and communications links. These communications links may be wired, optical, wireless, or any other device for communicating information. The communications network 1018 may be any suitable computer network, for example, a wide area network such as the Internet and / or a local area network such as Ethernet. The communications network 1018 may be wired and / or wireless, and the communications network may use encryption and decryption methods such as those available with virtual private networks. The communications network uses one or more communications interfaces that may receive data from other systems and transmit data to other systems. Embodiments of the communication interface typically include an Ethernet card, a modem (e.g., telephone, satellite, cable, or ISDN), an (asynchronous) Digital Subscriber Line (DSL) unit, a Firewire interface, a USB interface, and the like. One or more communication protocols, such as HTTP, TCP / IP, RTP / RTSP, IPX, and / or UDP, can be used.

[0081] 10, one or more processors 1002, machine-readable media 1004, user interface input devices 1012, user interface output devices 1014, and / or network interface 1016 can be communicatively coupled to each other using a bus subsystem 1020. Although the bus subsystem 1020 is shown diagrammatically as a single bus, alternative embodiments of the bus subsystem may use multiple buses. For example, a RAM-based main memory can communicate directly with a file storage system using a direct memory access (“DMA”) system. (Conclusion)

[0082] The detailed description has referred to the accompanying figures to illustrate exemplary embodiments consistent with this disclosure. References in this disclosure to "an exemplary embodiment" indicate that the described exemplary embodiment may include a particular feature, structure, or characteristic, but that not all exemplary embodiments necessarily include the particular feature, structure, or characteristic. Also, such phrases do not necessarily refer to the same exemplary embodiment. Furthermore, any feature, structure, or characteristic described in connection with an exemplary embodiment may be included independently or in any combination with features, structures, or characteristics of other exemplary embodiments, whether or not explicitly described.

[0083] The Detailed Description is not intended to be limiting. Rather, the scope of the present disclosure is defined solely by the following claims and their equivalents. It is understood that the Detailed Description section, and not the Abstract section, is intended to be used to interpret the claims. The Abstract section may describe one or more example embodiments of the present disclosure, but is not exhaustive, and thus is not intended to limit the present disclosure and the following claims and their equivalents in any way.

[0084] The exemplary embodiments described within this disclosure are provided for illustrative purposes and are not intended to be limiting. Other exemplary embodiments are possible, and modifications may be made to the exemplary embodiments while remaining within the spirit and scope of this disclosure. This disclosure is described with the help of functional components that illustrate implementations of defined functions and their relationships. The boundaries of these functional building blocks are arbitrarily defined herein for convenience of description. Alternative boundaries may be defined so long as the defined functions and relationships are appropriately performed.

[0085] Embodiments of the present disclosure may be implemented in hardware, firmware, a software application, or any combination thereof. Embodiments of the present disclosure may also be implemented as instructions stored on a machine-readable medium, which may be read and executed by one or more processors. A machine-readable medium may include any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computing network). For example, a machine-readable medium may include non-transitory machine-readable media, such as 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 may include a transitory machine-readable medium, such as an electrical, optical, acoustic, or other form of propagated signal (e.g., carrier wave, infrared signal, digital signal, etc.). Furthermore, firmware, software applications, routines, and instructions may be described herein as performing certain actions. However, it should be understood that such description is for convenience only and that such actions actually result from a computing device, processor, controller, or other device executing firmware, software applications, routines, instructions, etc.

[0086] The detailed description of the exemplary embodiments has fully revealed the general nature of the present disclosure, such that others, by applying the knowledge of those skilled in the art, may readily modify and / or adapt such exemplary embodiments for various applications without departing from the spirit and scope of the present disclosure and without undue experimentation. Moreover, such adaptations and modifications are intended to be within the meaning and equivalents of the exemplary embodiments, based on the teaching and guidance presented herein. It is to be understood that the terminology or phraseology herein is for purposes of description and not of limitation, as it would be interpreted by one of ordinary skill in the art in light of the teachings herein.

Claims

1. 1. An image capture system comprising:

1. A camera lens system comprising: capturing light associated with an image within a field of view of the camera lens system; steering a center of the camera lens system toward a periphery of an image sensor to direct the light toward the periphery of the image sensor; focusing the light captured by the camera lens system so that it is non-uniformly distributed onto the image sensor around the periphery of the image sensor; a camera lens system configured to: a camera assembly including the image sensor and configured to capture the light focused by the camera lens system onto the image sensor and provide a digital image signal related to the image; an image recording system configured to store the digital image signal; An image capture system comprising:

2. 10. The image capture system of claim 1, wherein the camera lens system is configured to steer the center of the camera lens system so as to produce the highest optical quality of the image within a three-dimensional media surface within the venue when the image is projected onto the venue.

3. The image capture system of claim 1 , wherein the camera lens system comprises an ultra-wide angle lens having a field of view of about 100 to about 180 degrees.

4. 10. The image capture system of claim 1, wherein the camera lens system comprises a perspective control lens configured to tilt, shift, or rotate the center of the camera lens system relative to the image sensor and steer the center of the camera lens system toward the periphery of the image sensor.

5. 2. The image capture system of claim 1, wherein the camera lens system is configured to focus the light onto the image sensor so that the light is more concentrated at the periphery of the image sensor compared to the center of the image sensor.

6. 6. The image capture system of claim 5, wherein the camera lens system is configured to concentrate the light to a first pixel density at the periphery of the image sensor and taper to a second pixel density at the center of the image sensor.

7. 10. The image capture system of claim 1, wherein the image sensor comprises a color sensor including a color mask configured to absorb undesired color wavelengths such that each pixel of the image sensor is sensitive to a particular color wavelength.

8. 1. A camera lens system comprising: a camera lens system configured to capture light associated with an image within a field of view of the camera lens system; A camera lens housing, steering a center of the camera lens system toward a periphery of an image sensor of the camera assembly to direct light captured by the center of the camera lens system toward the periphery of the image sensor; focusing light captured by the camera lens system so that the light is non-uniformly distributed onto the image sensor around the periphery of the image sensor; a camera lens housing configured to A camera lens system comprising:

9. 9. The camera lens system of claim 8, wherein the camera lens system is configured to steer the center of the camera lens system so as to produce the highest optical quality of the image within a three-dimensional media surface within the venue when the image is projected onto the venue.

10. The camera lens system of claim 8 , wherein the camera lens system comprises an ultra-wide angle lens having a field of view of about 100 to about 180 degrees.

11. The camera lens system of claim 10 , wherein the ultra-wide-angle lens comprises a fisheye lens.

12. 9. The camera lens system of claim 8, wherein the camera lens housing comprises a perspective control lens configured to tilt, shift, or rotate the center of the camera lens system relative to the image sensor and steer the center of the camera lens system toward the periphery of the image sensor.

13. 9. The camera lens system of claim 8, wherein the camera lens housing is configured to focus the light onto the image sensor so that the light is more concentrated near the periphery of the image sensor compared to a center of the image sensor.

14. 1. An image capture system comprising:

1. A camera lens system comprising: capturing light associated with an image within a field of view of the camera lens system; steering a center of the camera lens system toward a periphery of an image sensor of the camera assembly to direct light captured by the center of the camera lens system toward the periphery of the image sensor; focusing the light captured by the camera lens system so that it is non-uniformly distributed onto the image sensor around the periphery of the image sensor; a camera lens system configured to: a camera assembly configured to capture the light focused by the camera lens system onto the image sensor and provide a digital image signal related to the image; an image recording system configured to store the digital image signal; An image capture system comprising:

15. 15. The image capture system of claim 14, wherein the camera lens system is configured to steer the center of the camera lens system so as to produce the highest optical quality of the image within a three-dimensional media surface within the venue when the image is projected onto the venue.

16. The image capture system of claim 14 , wherein the camera lens system comprises an ultra-wide angle lens having a field of view of about 100 to about 180 degrees.

17. 15. The image capture system of claim 14, wherein the camera lens system comprises a perspective control lens configured to tilt, shift, or rotate the center of the camera lens system relative to the image sensor and steer the center of the camera lens system toward the periphery of the image sensor.

18. 15. The image capture system of claim 14, wherein the camera lens system is configured to focus the light onto the image sensor so that the light is more concentrated near the periphery of the image sensor compared to the center of the image sensor.

19. 15. The image capture system of claim 14, wherein the image sensor comprises a color sensor including a color mask configured to absorb undesired color wavelengths such that each pixel of the image sensor is sensitive to a particular color wavelength.

20. 15. The image capture system of claim 14, wherein the image recording system is configured to store the digital image signal as a raw camera image file having radiometric characteristics of the light captured by the image capture system.

21. 1. An image processing server for converting images for projection onto a media surface at a venue, said image processor comprising: a memory configured to store instructions; a processor configured to execute the instructions, the instructions, when executed by the processor, projecting three-dimensional coordinates of a plurality of pixels of the media surface onto two-dimensional coordinates of an 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 surface based on color information of the plurality of pixels of the image; providing the color information of the plurality of pixels to the venue and projecting the image onto the media surface; a processor, the processor configured to: An image processing server comprising:

22. 22. The image processing server of claim 21, 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.

23. 22. The image processing server of claim 21, wherein the color information for 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.

24. 22. The image processing server of claim 21 , wherein the instructions, when executed by the processor, configure the processor to interpolate the color information of pixels of the media plane of the plurality of pixels of the media plane by weighting and accumulating the color information of the plurality of pixels of the image that lie within a sample kernel space of a plurality of sample kernel spaces of the image.

25. 25. The image processing server of claim 24, 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 within the sample kernel space according to a probability density function.

26. the plurality of sample kernel spaces includes a first sample kernel space having a smaller two-dimensional area than a second sample kernel space; 25. The image processing server of claim 24, wherein the instructions, when executed by the processor, configure the processor to weight the color information of the plurality of pixels of the image such that the pixel of the media plane is located within the first sample kernel space when the pixel is closer to a top of the media plane or within the second sample kernel space when the pixel of the media plane is closer to a bottom of the media plane.

27. the first sample kernel space comprises a circle; 27. The image processing server of claim 26, wherein the second sample kernel space is associated with a Rosenbrock function.

28. 1. A method for transforming an image for projection onto a media surface at a venue, the method comprising: a computer system projecting three-dimensional coordinates of a plurality of pixels of the media surface onto two-dimensional coordinates of an image space of the image to provide a plurality of two-dimensional points projected onto the image; the computer system interpolating color information of the plurality of pixels of the media surface based on color information of the plurality of pixels of the image; the computer system providing the color information of the plurality of pixels to the venue and projecting the image onto the media surface; A method comprising:

29. 30. The method of claim 28, further comprising the computer system reconstructing the image from one or more digital image signals associated with the image.

30. 29. The method of claim 28, wherein the color information for 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.

31. 29. The method of claim 28, wherein the interpolating comprises interpolating the color information of the media plane pixels of the plurality of pixels of the media plane by weighting and accumulating color information of the plurality of pixels of the image located within a sample kernel space of a plurality of sample kernel spaces of the image.

32. 32. The image processing server of claim 31, wherein said interpolating further comprises weighting the color information of the plurality of pixels of the image located within the sample kernel space according to a probability density function.

33. the plurality of sample kernel spaces includes a first sample kernel space having a smaller two-dimensional area than a second sample kernel space; 32. The image processing server of claim 31 , wherein the interpolating further comprises weighting the color information of the plurality of pixels of the image that lie within the first sample kernel space when the pixel of the media plane is closer to a top of the media plane or within the second sample kernel space when the pixel of the media plane is closer to a bottom of the media plane.

34. the first sample kernel space comprises a circle; 34. The image processing server of claim 33, wherein the second sample kernel space is associated with a Rosenbrock function.

35. 1. An image processing system for converting an image for projection onto a media surface at a venue, said image processor system comprising: an image recording system configured to store one or more digital image signals associated with said image; an image processing server, reconstructing the image from the one or more digital image signals; projecting three-dimensional coordinates of a plurality of pixels of the media surface onto two-dimensional coordinates of an 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 surface based on color information of the plurality of pixels of the image; providing the color information of the plurality of pixels to the venue and projecting the image onto the media surface; an image processing server configured to An image processing system comprising:

36. 36. The image processing system of claim 35, wherein the color information for 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.

37. 36. The image processing system of claim 35, wherein the image processing server is configured to interpolate the color information of pixels of the media plane of the plurality of pixels of the media plane by weighting and accumulating color information of the plurality of pixels of the image that lie within a sample kernel space of a plurality of sample kernel spaces of the image.

38. 38. The image processing system of claim 37, wherein the image processing server is configured to weight the color information of the plurality of pixels of the image located within the sample kernel space according to a probability density function.

39. the plurality of sample kernel spaces includes a first sample kernel space having a smaller two-dimensional area than a second sample kernel space; 38. The image processing system of claim 37, wherein the image processing server is configured to weight the color information of the plurality of pixels of the image that lie within the first sample kernel space when the pixel of the media surface is closer to a top of the media surface or within the second sample kernel space when the pixel of the media surface is closer to a bottom of the media surface.

40. the first sample kernel space comprises a circle; 40. The image processing system of claim 39, wherein the second sample kernel space is associated with a Rosenbrock function.

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