Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "the warped image" in both lines 12 and 13. There is insufficient antecedent basis for this limitation in the claim. Since claim 1 recites “a warped image” in both lines 1 and 4-5, it cannot be determined which “a warped image” is being referred to when reciting “the warped image” in both lines 12 and 13. Similarly, as claim 1 recites “a warped image” in both lines 1 and 4-5, it cannot be determined whether “a warped image” in lines 4-5 is referring to the same “a warped image” in line 1. If they are the same “a warped image”, the Examiner suggests “a warped image” in lines 4-5 to be amended to recite “the warped image”. However, if they refer to different “a warped image”, the Examiner suggests “a warped image” in line 1 to be amended as “a first warped image”, and “a warped image” in lines 4-5 to be amended as “a second warped image”, with “the warped image” in lines 12 and 13 to be amended in a similar fashion to give basis to the limitations. To advance compact prosecution, the Examiner interprets “a warped image” in both lines 1 and 4-5 to refer to the same “a warped image”.
Claims 2-7, 17, and 19 incorporate independent claim deficiency from claim 1 and thus also rejected under 112(b).
Claims 8 and 15 recite substantially similar limitations to claim 1, therefore, are also rejected under 112(b).
Claims 9-14, 16, 18, and 20 incorporate independent claim deficiency from claim 8 and thus also rejected under 112(b).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-4, 8-11, 15, 17, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Hakim et al. (U.S. Patent No. 11,989,856, hereinafter Hakim), in view of Martin Brualla et al. (US 2022/0398705 A1, hereinafter Martin).
Regarding claim 1, Hakim teaches a method of artefact correction of a ([Abstract] “Aspects of embodiments pertain to a method for reducing a subjective visual artefact when displaying binocular overlapping images to a user of a binocular display system”, where “Some types of HMD systems are operable to display a computer-generated symbol while at same time allowing the viewer to see through the HMD system's visor.” [col. 1, lines 27-30], “Aspects of disclosed embodiments concern binocular display devices, systems and methods. The term “binocular display system” pertains to a system that employs binocular viewing optics for projecting respective images towards a user (also: viewer). Binocular display system can include, for example, binocular head-mountable display (HMD) systems.” [col. 2, lines 45-51], and “In embodiments, a binocular display device of a binocular display system comprises an image display unit having a plurality of pixels for displaying right and left-eye source images.” [col. 3, lines 14-17]. Note: “the binocular display system” is mapped to the VST device).
determining a location of at least one artefact… from a plurality of image frames captured by the plurality of ([col. 5, lines “In some embodiments, an eye model may be used in conjunction with an eye tracker to estimate the position of the perceived luning artefacts for adaptively applying artefact correction in accordance with the user's eye gaze direction and the associated eye model.”)
determining one or more correction parameters for the at least one artefact based on the determined location; ([col. 13, lines 21-26] “In the event the perceived artefact brightness magnitude difference exceeds an artefact correction criterion, the pixel parameter value may be applied at the corresponding pixel position(s). In some embodiments, a pixel parameter value may be modified in accordance with an artefact correction function, e.g., as described herein.”, where “artefact correction parameter values (e.g., one or more pixel parameter values)” [col. 3, lines 50-51])
identifying image data… from at least one image frame captured by at least one of the plurality of ([col. 5, lines 10-17] “Prior to modifying the one or more pixel and/or image display parameter values, the binocular display system's performance characteristics may be determined. This may comprise localizing, in the viewer's Field-of-View (FOV), regions of occurrence of the perceptual artefact, e.g., by determining the border area location between overlapping and non-overlapping regions of the left and right-hand observed images.”)
and correcting the at least one artefact in the ([col. 4, lines 45-61] “In a further example, to reduce or eliminate luning artefacts, a parameter value of an image display region associated with (e.g., mapped to) a monocular viewing region may be altered (e.g., image display refresh rate increased) such to increase perceived pixel brightness; or an image display parameter value associated with (e.g., mapped to) a binocular viewing region may be altered (e.g., image display intensity may be decreased) such to reduce perceived pixel brightness; or the parameter value of a display region associated with (e.g., mapped) to a monocular viewing region may be altered (e.g., image display rate may be increased) to increase perceived pixel brightness and, at the same time, a parameter value of a display region associated with (e.g., mapped to) a binocular viewing region may be altered (e.g., pixel output intensity may be decreased) to reduce perceived pixel brightness in order to diminish or eliminate luning artefacts.”).
Hakim fails to teach a method of artefact correction of a warped image comprising a plurality of primary imaging devices and a plurality of secondary imaging devices,, a corresponding depth map from a warped image generated from a plurality of image frames, and identifying image data and corresponding depth information from at least one image frame captured by at least one of the plurality of secondary imaging devices based on… the corresponding depth map. However, this is known in the art as taught by Martin.
Martin teaches a method of artefact correction of a warped image ([0008] “In one general aspect, systems and methods are described for receiving a plurality of input images, receiving a plurality of depth images associated with a target subject in at least one of the plurality of input images, receiving a plurality of view parameters for generating a virtual view of the target subject, and generating a plurality of warped images based on the plurality of input images, the plurality of view parameters, and at least one of the plurality of depth images.”, where “In some implementations, the systems and methods described herein may also employ occlusion reasoning to correct for artifacts in the synthesized novel views.” [0006])
comprising a plurality of primary imaging devices and a plurality of secondary imaging devices, ([0061] “In some implementations, each systems 202A, 202B, and 202N include three or more camera pods that each include a depth camera (e.g., depth sensor 206 and/or one or more pairs of IR cameras whose content is analyzed using stereo algorithms to infer a depth image) and one or more color cameras.”. Note: the primary imaging devices is mapped to color cameras, and the secondary imaging devices is mapped to the depth cameras.)
a corresponding depth map from a warped image generated from a plurality of image frames ([0008] “In one general aspect, systems and methods are described for receiving a plurality of input images, receiving a plurality of depth images associated with a target subject in at least one of the plurality of input images, receiving a plurality of view parameters for generating a virtual view of the target subject, and generating a plurality of warped images based on the plurality of input images, the plurality of view parameters, and at least one of the plurality of depth images.”)
identifying image data and corresponding depth information from at least one image frame captured by at least one of the plurality of secondary imaging devices based on… the corresponding depth map ([0010] “In some implementations, the systems and methods may further comprise providing, to the neural network, a difference in depth between the geometrically fused model and a depth observed in the plurality of depth images, and the method further comprising correcting for detected occlusions in the synthesized image based on the difference in depth. In some implementations, the plurality of input images are color images captured according to predefined view parameters associated with at least one camera that captured the plurality of input images and/or the plurality of depth images each including a depth map associated with at least one camera that captured at least one of the plurality of input images, at least one occlusion map, and/or a depth map associated with a ground truth image captured by at least one witness camera at a time corresponding to capture of at least one of the plurality of input images.”)
Martin is analogous to the claimed invention, as both relate to artifact correction of warped images using depth information. Martin further teaches that “The systems and methods described herein may generate novel color images that have fewer artifacts than conventional systems. For example, the systems and methods described herein may correct for particular image noise and loss function analysis to generate novel images with fewer depth inaccuracies and fewer occlusions” [0030]. Therefore, it would be obvious for one of ordinary of skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Martin to Hakim to have less artifacts via more accurate depth data and less occlusions.
Regarding claim 2, the combination of Hakim and Martin teaches the method as claimed in claim 1, further comprising: prior to correcting the at least one artefact in the warped image, modifying the image data based on the one or more correction parameters, wherein the one or more correction parameters comprise at least one of a resolution, a sharpness, a colour, and a luma component (Hakim; [col. 4, lines 15-22] “The expression “pixel parameter”, as used herein, may refer any one of the following: pixel output intensity, pixel color, pixel refresh rate, number of pixels allocated for projection to the left-eye monocular viewing region, the right-eye monocular viewing region and/or the binocular viewing region, and/or the like. It is noted that a pixel may comprise two or more subpixels, e.g., for generating a desired color to correct for a perceived image artefact.”)
Regarding claim 3, the combination of Hakim and Martin teaches the method as claimed in claim 1, wherein the identifying the image data from the at least one image frame captured by the at least one of the plurality of secondary imaging devices comprises: identifying at least one region from the at least one image frame based on the determined location of the at least one artefact in the warped image and the one or more correction parameters (Hakim; [col. 13, lines 21-26] “In the event the perceived artefact brightness magnitude difference exceeds an artefact correction criterion, the pixel parameter value may be applied at the corresponding pixel position(s). In some embodiments, a pixel parameter value may be modified in accordance with an artefact correction function, e.g., as described herein.”, where “artefact correction parameter values (e.g., one or more pixel parameter values)” [col. 3, lines 50-51]).
Regarding claim 4, the combination of Hakim and Martin teaches the method as claimed in claim 1, wherein the correcting the at least one artefact in the warped image comprises: generating a scene at the determined location of the at least one artefact by fusing the image data from the at least one image frame with the warped image (Martin; [0003] “In general, the warping process can cause geometric inaccuracies and view and/or image-dependent effects that may produce artifacts when contributions from different input views are blended together. The systems and methods described herein use a deep learning technique that employs neural networks (NNs) to blend image content for image-based rendering of novel views. Particular blend weights are learned and used to combine input image contributions to a final synthesized view.”).
Martin is analogous to the claimed invention, as both relate to artifact correction of warped images using depth information. Martin further teaches that “The blend weights are generated to provide the advantage of generating synthesized images that exhibit reduced view and/or image-dependent effects and a reduced number of image artifacts.” [0003]. Therefore, it would be obvious for one of ordinary of skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Martin to the combination of Hakim and Martin to have reduce the number of artifacts in the synthesized image.
Regarding claim 8, claim 8 recites substantially similar limitations to claim 1, but in a system form. The combination of Hakim and Martin further teaches a system for artefact correction of a warped image in a video see through (VST) device, (Hakim; [col. 3, lines 45-52] “In an embodiment, the binocular display system comprises a display unit control engine that is operable to reduce, based on system performance characteristics of the binocular display system, the viewer's perception of a subjective visual artefact in the perceived right and left-hand observation images by modifying artefact correction parameter values (e.g., one or more pixel parameter values) of the left and/or right-hand source images.”).
the system comprising: a plurality of primary imaging devices; a plurality of secondary imaging devices; (Martin; [0060] “The system 200 may include one or more 3D systems 202. In the depicted example, 3D systems 202A, 202B through 202N are shown, where the index N indicates an arbitrary number.”, where “In some implementations, each systems 202A, 202B, and 202N include three or more camera pods that each include a depth camera (e.g., depth sensor 206 and/or one or more pairs of IR cameras whose content is analyzed using stereo algorithms to infer a depth image) and one or more color cameras.” [0061]. Note: the primary imaging devices is mapped to color cameras, and the secondary imaging devices is mapped to the depth cameras).
a memory storing instructions; and at least one processor communicably coupled with the memory, wherein, by executing the instructions stored on the memory, the at least one processor is configured to: (Hakim; [col. 6, lines 60-66] “For instance, processor 1300 may execute program code instructions 1210 stored in memory 1200 resulting in DUC engine 1500 which is operable to implement a method for reducing a subjective visual artefact when displaying binocular overlapping images to a user of a binocular display system, which may be a head-mountable display (HMD) system.”)
Martin is analogous to the claimed invention, as both relate to artifact correction of warped images using depth information. Martin further teaches “the systems and methods described herein may correct for particular image noise and loss function analysis to generate novel images with fewer depth inaccuracies and fewer occlusions.” [0030]. Therefore, it would be obvious for one of ordinary of skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Martin to the combination of Hakim and Martin in order to have accurate depth data with less occlusions.
Regarding claim 9, claim 9 recites substantially similar limitations to claim 2, therefore, rejected under the same rationale as claim 2.
Regarding claim 10, claim 10 recites substantially similar limitations to claim 3, therefore, rejected under the same rationale as claim 3.
Regarding claim 11, claim 11 recites substantially similar limitations to claim 4, therefore, rejected under the same rationale as claim 4.
Regarding claim 15, claim 15 recites substantially similar limitations to claim 1, but in a medium form. The combination of Hakim and Martin further teaches a non-transitory computer-readable recording medium in which a program for executing an artefact correction method of a video see through (VST) device comprising a plurality of primary imaging devices and a plurality of secondary imaging devices, the artefact correction method comprising: (Hakim; [col. 22, lines 61-66] “The methods and/or processes disclosed herein may be implemented as a computer program product that may be tangibly embodied in an information carrier including, for example, in a non-transitory tangible computer-readable and/or non-transitory tangible machine-readable storage device.”).
Regarding claim 17, the method as claimed in claim 1, further comprising: determining the depth map including a depth value for a plurality of pixels from an image captured by one of the plurality of secondary imaging devices and corresponding to the warped image (Martin; [0082] “In operation, the system 200 may receive a stereo-fusion pipeline that produces (1) depth maps corresponding to each of three color camera images and (2) depth values from a target viewpoint to a nearest surface point determined for each output pixel, Dt in a synthesized view. For example, an image capture system may include at least three camera pods. Each camera pod may include one or more color cameras and a depth camera (e.g., cameras 204, depth sensor 206). In some implementations, the image capture system may additionally include a witness camera pod. In this example, the system may perform geometric warping to transform information from the three camera pods into a target image space for the witness camera pod.”).
Martin is analogous to the claimed invention, as both relate to artifact correction of warped images using depth information. Martin further teaches “the systems and methods described herein may correct for particular image noise and loss function analysis to generate novel images with fewer depth inaccuracies and fewer occlusions.” [0030]. Therefore, it would be obvious for one of ordinary of skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Martin to the combination of Hakim and Martin in order to have accurate depth data with less occlusions.
Regarding claim 18, claim 18 recites substantially similar limitations to claim 17, therefore, rejected under the same rationale as claim 17.
Regarding claim 20, claim 20 recites substantially similar limitations to claim 4, therefore, rejected under the same rationale as claim 4.
Claims 5 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Hakim in view of Martin, and further in view of Ko et al. (KR 101415147 B1, hereinafter Ko).
Regarding claim 5, the combination of Hakim and Martin teaches the method as claimed in claim 1, but fails to teach wherein the determining the location of the at least one artefact in the warped image comprises: identifying a plurality of blank pixels and corresponding position coordinates in the warped image; classifying the plurality of blank pixels as the at least one artefact; and determining the location of the at least one artefact based on the position coordinates of the plurality of blank pixels. However, this is known in the art as taught by Ko.
Ko teaches wherein the determining the location of the at least one artefact in the warped image comprises: identifying a plurality of blank pixels and corresponding position coordinates in the warped image; classifying the plurality of blank pixels as the at least one artefact; ([0117] “Here, ST(x,y) and SD(x,y) are the color and depth values of the hole to be compensated at the (x,y) coordinate”, where “Holes occur due to the occluded areas created after 3D warping. Typically, if there are multiple reference point cameras, occluded areas can be identified and compensated for from other reference points” [0131]. Note: the holes are mapped to the blank pixels.)
and determining the location of the at least one artefact based on the position coordinates of the plurality of blank pixels ([0118] “(x,y) are the coordinates of the hole to be filled”).
Ko is analogous to the claimed invention, as both relate to correcting artifacts of warped images. Ko further teaches that “Therefore, since holes and boundary noise as described above are factors that degrade the quality of the generated virtual viewpoint image, there is an urgent need for post-processing techniques to improve the quality of the virtual viewpoint image by removing these elements” [0018]. Therefore, it would be obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Ko to the combination of Hakim and Martin in order to remove the degradation of quality of the images.
Regarding claim 12, claim 12 recites substantially similar limitations to claim 5, therefore, rejected under the same rationale as claim 5.
Claims 6-7, 13-14, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Hakim in view of Martin, and further in view of Kim et al. (U.S. Patent No. 12,015,755, hereinafter Kim).
Regarding claim 6, the combination of Hakim and Martin teaches the method as claimed in claim 1, but fails to teach wherein the identifying the image data from the at least one image frame captured by the at least one of the plurality of secondary imaging devices comprises: receiving a plurality of image frames captured by the plurality of secondary imaging devices; selecting the at least one image frame from the plurality of image frames based on the determined location of the at least one artefact and the one or more correction parameters; and identifying the image data from the at least one image frame. However, this is known in the art as taught by Kim.
Kim teaches wherein the identifying the image data from the at least one image frame captured by the at least one of the plurality of secondary imaging devices comprises: receiving a plurality of image frames captured by the plurality of secondary imaging devices; ([col. 13, lines 35-37] “The receiver 930 receives fisheye images of a subject captured through the first fisheye camera 911 to the fourth fisheye camera 922.”)
selecting the at least one image frame from the plurality of image frames based on the determined location of the at least one artefact and the one or more correction parameters; ([col. 13, lines 38-41] “The selector 940 selects a single fisheye camera from among remaining fisheye cameras for each pixel of a preset reference fisheye image among the received fisheye images using a sweep volume for preset distance candidates.”, where “The present invention may select only a best camera from among three cameras (c1, c2, and c3) for each pixel in a reference view. When a plurality of cameras has a field of view capable of covering a pixel in a reference frame, a camera having a highest distance discrimination power may be selected.” [col. 9, lines 5-10])
and identifying the image data from the at least one image frame. ([col. 13, lines 60-67 – col. 14, lines 1-5] “Here, the generator 950 may generate a final 360-degree color image in real time by inpainting a missing region in the 360-degree color image using a background of the 360-degree color image. For example, in a process of generating the 360-degree color image, the generator 950 may determine an inpainting direction by determining a foreground direction and a background direction in the 360-degree color image, may compute an inpainting kernel based on the determined inpainting direction and an occlusion direction of the missing region, and may inpaint the missing region using a depth value of a background of the 360-degree color image by applying the computed inpainting kernel to the distance map.”)
Kim is analogous to the claimed invention, as both relate to correcting artifacts from stereo images. Kim further teaches “To achieve real-time performance, the present invention may employ a camera selection method that provides a regional best camera pair for a search correspondence in the sphere sweep volume with reference to a reference camera.” [col. 8, line 67 – col. 9, lines 1-4]. Therefore, it would be obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Kim to the combination of Hakim and Martin to select the best camera with the best frame in order to achieve real-time performance.
Regarding claim 7, the combination of Hakim, Martin, and Kim teaches the method as claimed in claim 1, wherein the identifying the image data from the at least one image frame captured by the at least one of the plurality of secondary imaging devices comprises: selecting at least one of the plurality of secondary imaging devices based on the determined location of the at least one artefact and the one or more correction parameters; ([col. 13, lines 38-41] “The selector 940 selects a single fisheye camera from among remaining fisheye cameras for each pixel of a preset reference fisheye image among the received fisheye images using a sweep volume for preset distance candidates.”, where “The present invention may select only a best camera from among three cameras (c1, c2, and c3) for each pixel in a reference view. When a plurality of cameras has a field of view capable of covering a pixel in a reference frame, a camera having a highest distance discrimination power may be selected.” [col. 9, lines 5-10])
and identifying the image data from the at least one image frame captured by the at least one selected secondary imaging device. ([col. 13, lines 60-67 – col. 14, lines 1-5] “Here, the generator 950 may generate a final 360-degree color image in real time by inpainting a missing region in the 360-degree color image using a background of the 360-degree color image. For example, in a process of generating the 360-degree color image, the generator 950 may determine an inpainting direction by determining a foreground direction and a background direction in the 360-degree color image, may compute an inpainting kernel based on the determined inpainting direction and an occlusion direction of the missing region, and may inpaint the missing region using a depth value of a background of the 360-degree color image by applying the computed inpainting kernel to the distance map.”)
Kim is analogous to the claimed invention, as both relate to correcting artifacts from stereo images. Kim further teaches “To achieve real-time performance, the present invention may employ a camera selection method that provides a regional best camera pair for a search correspondence in the sphere sweep volume with reference to a reference camera.” [col. 8, line 67 – col. 9, lines 1-4]. Therefore, it would be obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Kim to the combination of Hakim and Martin to select the best camera with the best frame in order to achieve real-time performance.
Regarding claim 13, claim 13 recites substantially similar limitations to claim 6, therefore, rejected under the same rationale as claim 6.
Regarding claim 14, claim 14 recites substantially similar limitations to claim 7, therefore, rejected under the same rationale as claim 7.
Regarding claim 19, claim 19 recites substantially similar limitations to claim 4 and 6, therefore rejected under the same rationales as claims 4 and 6.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Hakim in view of Martin, and further in view of Freeman et al. (US 2018/0192032 A1, hereinafter Freeman).
The combination of Hakim and Martin teaches the system as claimed in claim 8, wherein the plurality of primary imaging devices comprise a plurality of red-green-blue (RGB) cameras, (Martin; [0060] “The system 200 may include one or more 3D systems 202. In the depicted example, 3D systems 202A, 202B through 202N are shown, where the index N indicates an arbitrary number.”, where “In some implementations, each systems 202A, 202B, and 202N include three or more camera pods that each include a depth camera (e.g., depth sensor 206 and/or one or more pairs of IR cameras whose content is analyzed using stereo algorithms to infer a depth image) and one or more color cameras.” [0061]. Note: the primary imaging devices is mapped to color cameras, and the secondary imaging devices is mapped to the depth cameras).
wherein, based on an arrangement of the plurality of (Martin; [0034] “The depth difference may be generated using a view from a color camera between a closest surface to the novel view and that of the camera view. The depth difference may be used for occlusion reasoning in order to correct for occluded views and/or other errors in generated images.” Note: the occluded views are the regions not within the field of view of the RGB cameras).
Martin is analogous to the claimed invention, as both relate to artifact correction of warped images using depth information. Martin further teaches “the systems and methods described herein may correct for particular image noise and loss function analysis to generate novel images with fewer depth inaccuracies and fewer occlusions.” [0030]. Therefore, it would be obvious for one of ordinary of skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Martin to the combination of Hakim and Martin in order to have accurate depth data with less occlusions.
The combination of Hakim and Martin fails to teach wherein the plurality of secondary imaging devices comprise a plurality of simultaneous localization and mapping (SLAM) cameras, as Martin teaches depth cameras instead. However, this is known in the art as taught by Freeman.
Freeman teaches that “In many modern smart phones, disparity maps are generating using a simultaneous localization and mapping (SLAM) software. SLAM software tracks a set of targeted pixel points through successive camera frames and uses these tracks to triangulate a positional coordinate in real space. Simultaneously, the estimated positions in real space are used to calculate the camera positions which could have observed them.” [0006]. Freeman is also analogous to the claimed invention, as both relate to projecting 3D virtual stereoscopic images with depth mapping. Therefore, it would be obvious for one of ordinary skill in the art to incorporate the teachings of Freeman to the combination of Hakim and Martin to use SLAM cameras for depth mapping instead of the depth cameras as taught by Martin in order to be able to track precise locations of pixels in real space.
Conclusion
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/ALICIA HA/Examiner, Art Unit 2611
/KEE M TUNG/Supervisory Patent Examiner, Art Unit 2611
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