CTNF 18/860,839 CTNF 83016 DETAILED ACTION This action is in response to communications: Preliminary-Amendment filed October 28, 2024. Claims 1-12 and 14-16 are pending in this case. Claims 5, 14, and 15 have been amended. Claim 13 has been newly cancelled. Claim 16 has been newly added. This action is made Non-Final. Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Priority 02-26 AIA Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Information Disclosure Statement The information disclosure statements (IDS) submitted on November 26, 2024 and March 14, 2025 were filed after the filing date of the application on October 28, 2024. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner. Drawings 06-37 AIA The drawings were received on October 28, 2024 . These drawings are accepted . Specification 06-11 AIA The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-21-aia AIA Claim (s) 1, 2, 6, 14, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over REZAIIFAR et al. (US 2019/0266789) . As to claim 1, REZAIIFAR et al. disclose an image rendering method ( Figure 1, steps performed by each of camera 101, dynamic lighting system 102 including image segmentation engine 104, depth modeling engine 106 (e.g. as depth modeling engine 206 of Figure 2), and dynamic light determination engine 108 (e.g. as dynamic light determination engine of Figure 5), and output engine 103, e.g. Figures 11-13 ), comprising: obtaining an object depth map ( e.g. Figures 5, 6A, 8A, 9A, dense depth map 518 ) and an object normal map ( Figure 8B, normal map ) of a target object in an image ( e.g. Figures 2, 5, 6C, image of object 210/510 captured via camera 101 )( e.g. via depth modeling engine 106 and dynamic light determination engine 108 of dynamic lighting system 102, where Figure 2, [0083] notes input data is provided to the depth modeling engine 206, e.g. image of object 210, segmentation (foreground) mask 212, (x,y) coordinates of object feature points of model 214, dense depth map of object model 216, which generates a dense depth map 218, e.g. an object-specific depth map (see additional text of Figure 2, [0080]-[0088]), [0089], [0090] notes the dense depth map of an object output from the depth modeling engine 206 can be used, along with the input image and the segmentation mask of the object, to determine dynamic lighting for the object, e.g. via dynamic light determination engine 108, where Figure 5, [0094] notes the dynamic light determination engine 108 includes a normal pass 525 that generates a normal map for the object in the input object image 510, the dense depth map 518 is used to produce the normal map ); determining occlusion information ( Figure 9B, ambient occlusion (AO) map ) based on the object depth map ( e.g. dense depth map 518 )( e.g. via dynamic light determination engine 108 of dynamic lighting system 102, where Figure 5, [0095] notes dynamic light determination engine 108 includes an occlusion pass 526 that determines ambient occlusion (AO) to generate an AO map (“occlusion information”), the depth map data of the dense depth map 518 is used to calculate the AO map ); determining illumination information ( e.g. light values ) based on the object normal map ( e.g. normal map )( e.g. via dynamic light determination engine 108 of dynamic lighting system 102, where Figure 5, [0091] notes determining light values (“illumination information”) for each point of the object in the image, and [0092] notes tunable parameters 528 used to determine the light values, which may include lighting characteristics that can be dynamically adjusted by a user, e.g. position 531 of a light source relative to the object of interest, a direction 532 of the light source relative to the object of interest, a color 533 (or hue) of the light from the light source, an intensity 534 of the light from the light source, and a roughness 535 of the object surface, where [0096]-[0099] notes light pass 527 of the light determination engine uses all the previously generated data, e.g. from noise pass 524, normals pass 525, and the occlusion pass 526, as well as the tunable parameters 528 to simulate the effects of the light hitting the object at the particular position, thus based on at least the normal map generated via normal pass 525, and given these inputs for the given point on the object, the light pass 527 can compute the lighting value for which that point needs to have in terms of illumination ); and rendering the target object in the image based on the occlusion information and the illumination information to obtain a target image ( Figures 10A, image of light simulation result produced by the light pass 527 based on certain tunable parameter values, Figure 10B, image of light simulation result produced by the light pass 527 based on different tunable parameter values )( e.g. rendering results from dynamic lighting system 102 via output engine 103, where Figure 5, [0096]-[0099] notes light pass 527 of the light determination engine uses all the previously generated data, e.g. from noise pass 524, normals pass 525, and the occlusion pass 526, as well as the tunable parameters 528 to simulate the effects of the light hitting the object at the particular position, thus based on at least the ambient occlusion (AO) map (“occlusion information”), the light pass 527 then generates a result 529 that includes an image with the determined light values, thus further based on the light values (“illumination information”), where [0076] notes output engine 103 outputs the results from the dynamic lighting system 102, e.g. an image with a dynamic lighting effect ). As noted above, REZAIIFAR et al. disclose each of the dense depth map and normal map generated by the dynamic lighting system, where the dense depth map and normal map may be used to determine ambient occlusion and light values as described, thus obvious that the previous results generated are used as input data to determine ambient occlusion and light values as described, yielding predictable results, without changing the scope of the invention. As to claim 2, REZAIIFAR et al. disclose the determining occlusion information based on the object depth map ( e.g. determining ambient occlusion (AO) map (“occlusion information”) via occlusion pass 526 of dynamic light determination engine 108 based on dense depth map of object 518 ) comprises: obtaining a body depth map of a scene where the target object is located ( e.g. as noted in claim 1, the resulting dense depth map 218 is referred to as the object-specific depth map, which is generated based on input data provided to the depth modeling engine 206, e.g. image of object 210, segmentation (foreground) mask 212, (x,y) coordinates of object feature points of model 214, dense depth map of object model 216, where [0077], [0080], [0083] notes the segmentation mask 212 is generated by segmentation engine 104 by segmenting the image into a foreground region (including the at least one object) and a background region (including other regions of the image not including the at least one object), the segmentation mask 212 includes foreground pixels for pixels corresponding to the object of interest and background pixels for the rest of the image, the segmentation mask 212 can be used by the depth modeling engine 206 to separate the foreground region from the background region so that only the foreground pixels of the object are processed, e.g. so the system 102 knows where the pixels of the object are, thus may be considered to obtain a “body depth map” via the segmentation mask ); and determining the occlusion information based on the body depth map and the object depth map ( e.g. as noted in claim 1 and illustrated in Figure 5, the ambient occlusion (AO) map determined in the occlusion pass 526 of the dynamic light determination engine 108 based on the image of object 510, dense depth map of object, e.g. object-specific depth map 518, and segmentation (foreground) mask 512 ). As to claim 6, REZAIIFAR et al. disclose the determining illumination information based on the object normal map ( e.g. determining light values (“illumination information”) via light pass 527 of the dynamic light determination engine 108 based on the normal map generated by normal pass 525 ) comprises: smoothing normal information in the object normal map ( e.g. a roughness 535 (or “smoothness”) of the object surface ); obtaining an illumination direction of the 3D point of the target object ( e.g. direction 532 of the light source relative to the object of interest ); and determining illumination information of the 3D point based on the illumination direction and the smoothed normal information ( e.g. as noted in claim 1, [0091] notes determining light values for each point of the object in the image, and [0092] notes tunable parameters 528 used to determine the light values, which may include lighting characteristics may include position 531 of a light source relative to the object of interest, a direction 532 of the light source relative to the object of interest, a color 533 (or hue) of the light from the light source, an intensity 534 of the light from the light source, and a roughness 535 of the object surface, where the roughness 535 of the object surface determines the reflectance of the surface, e.g. smoother surfaces tend to be more reflective than more textured surfaces, [0096]-[0099] notes given these inputs for the given point on the object, the light pass 527 can compute the lighting value for which that point needs to have in terms of illumination ). As to claim 14, REZAIIFAR et al. disclose an electronic device ( Figure 1, computing device 100, where [0075] notes computing device 100 may be any suitable electronic device ), comprising: one or more processing apparatuses ( e.g. camera 101, dynamic lighting system 102 including image segmentation engine 104, depth modeling engine 106 (e.g. as depth modeling engine 206 of Figure 2), and dynamic light determination engine 108 (e.g. as dynamic light determination engine of Figure 5), and output engine 103 ); and a storage apparatus ( e.g. memory as “computer-readable medium” ), configured to store one or more programs ( e.g. code, instructions, and/or data ), wherein the one or more programs ( e.g. code, instructions, and/or data ), when executed by the one or more processing apparatuses ( e.g. one or more processors, e.g. engines described above ), cause the one or more processing apparatuses to implement an image rendering method ( [0076] notes computing device 100 can include additional components not illustrated, e.g. memory, one or more processors, and one or more transceivers for wirelessly communicating data, where [0070], [0071] notes computer-readable medium stores code, instructions, and/or data, which may be executed by one or more processors to perform the method(s) as described ) , the image rendering method comprising …the steps performed in the image rendering method of claim 1. Please see the rejection and rationale of claim 1. As to claim 15, REZAIIFAR et al. disclose a computer-readable medium ( e.g. memory as “computer-readable medium” ), storing a computer program ( e.g. code, instructions, and/or data ), wherein the computer program ( e.g. code, instructions, and/or data ), when executed by a processing apparatus ( e.g. one or more processors, including camera 101, dynamic lighting system 102 including image segmentation engine 104, depth modeling engine 106 (e.g. as depth modeling engine 206 of Figure 2), and dynamic light determination engine 108 (e.g. as dynamic light determination engine of Figure 5), and output engine 103 of computing device 100 of Figure 1 ), causes implementing an image rendering method ( [0076] notes computing device 100 can include additional components not illustrated, e.g. memory, one or more processors, and one or more transceivers for wirelessly communicating data, where [0070], [0071] notes computer-readable medium stores code, instructions, and/or data, which may be executed by one or more processors to perform the method(s) as described ) , the image rendering method comprising …the steps performed in the image rendering method of claim 1. Please see the rejection and rationale of claim 1 . Allowable Subject Matter 12-151-08 AIA 07-43 12-51-08 Claim s 3-5, 7-12, and 16 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. 13-03-01 AIA The following is a statement of reasons for the indication of allowable subject matter: Regarding claims 3, 5, 7, and 12, the prior art of record fails to teach or suggest the limitations of each of these claims as recited. Dependent claims 4 and 16 are indicated allowable for depending upon claim 3. Dependent claims 8-11 are indicated allowable for directly or indirectly depending upon claim 7 . Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to JACINTA M CRAWFORD whose telephone number is (571)270-1539. The examiner can normally be reached 8:30a.m. to 4:30p.m. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, King Y. Poon can be reached at (571)272-7440. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JACINTA M CRAWFORD/Primary Examiner, Art Unit 2617 Application/Control Number: 18/860,839 Page 2 Art Unit: 2617 Application/Control Number: 18/860,839 Page 3 Art Unit: 2617 Application/Control Number: 18/860,839 Page 4 Art Unit: 2617 Application/Control Number: 18/860,839 Page 5 Art Unit: 2617 Application/Control Number: 18/860,839 Page 6 Art Unit: 2617 Application/Control Number: 18/860,839 Page 7 Art Unit: 2617 Application/Control Number: 18/860,839 Page 8 Art Unit: 2617 Application/Control Number: 18/860,839 Page 9 Art Unit: 2617
Prosecution Insights