CTNF 18/670,373 CTNF 82825 DETAILED ACTION 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. Response to Arguments Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Claim Rejections - 35 USC § 103 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. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim (s) 1, 4, 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Henden et al. (US 2026/0017875 A1) . Consider claim 1 , Reitmayr teaches one or more processors comprising: processing circuitry to: compute, based at least on sensor data generated using one or more sensors of an ego-machine in an environment, a three-dimensional (3D) surface topology of the environment ([0072] – [0085]); generate an updated 3D surface topology of the environment based at least one applying the sensor data to the 3D surface topology (At block 612 , the process 600 includes updating a 3D representation of the scene using the three-dimensional representation of the portion of the scene. For instance, the scene representation system 200 can update the 3D representation of the scene using the 3D representation of the portion of the scene. The 3D representation of the scene can include additional representations of additional portions of the scene generated based on additional image data associated with the additional portions of the scene. [0072] – [0085]). However, Reitmayr does not explicitly teach generate a two-dimensional (2D) visualization of the updated 3D surface topology. Henden teaches generate a two-dimensional (2D) visualization of the updated 3D surface topology (At 250 , the method 200 can render, from the one or more corresponding portions of the 3D model, one or more 2D images each corresponding to a respective viewpoint of the one or more viewpoints. For example, the method 200 can render 2D video by capturing images from a simulated viewpoint over time. [0090] – [0095]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of generating a two-dimensional (2D) visualization of the updated 3D surface topology because such incorporation would allow autonomous objects to more accurately navigate the real world. [0004]. Consider claim 4 , Reitmayr teaches the processing circuitry further to represent the 3D surface topology of the environment using a 3D signed distance function ([0054] – [0055] and [0074]). Consider claim 11 , Reitmayr teaches the one or more processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D asset; a system for performing deep learning operations; a system for performing real-time streaming; a system for generating or presenting one or more augmented reality content, virtual reality content, or mixed reality content; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for generating synthetic data; a system for generating synthetic data using AI; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources ([0029], [0084]) . 07-21-aia AIA Claim (s) 2 and 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Henden et al. (US 2026/0017875 A1) and Subasingha et al. (US 2022/0180539 A1) . Consider claim 2 , the combnation of Reitmayr and Henden teaches all the limitations in claim 1 but does not explicitly teach the processing circuitry further to apply the sensor data to the 3D surface topology based at least on back-projecting one or more values of the sensor data onto the 3D surface topology. Subasingha teaches the processing circuitry further to apply the sensor data to the 3D surface topology based at least on back-projecting one or more values of the sensor data onto the 3D surface topology (In some implementations, the sensor computing device(s) 508 can also determine the sensor data in an unprojected format. For example, an unprojection can refer to a transformation from a two-dimensional frame (or a 5.5-dimensional frame) of reference into a three-dimensional frame of reference or a three-dimensional surface, while a projection can refer to a transformation from a three-dimensional frame of reference into a two-dimensional frame of reference. In some instances, techniques described herein can determine a location of the sensor system(s) 506 relative to the three-dimensional surface and unproject the data into the three-dimensional frame based at least in part on the depth information, pixel coordinate, intrinsic and extrinsic information associated with the sensor system(s) 506 (e.g., focal length, center, lens parameters, height, direction, tilt, etc.), and the known location of the sensor system(s) 506 . In some instances, the depth information can be unprojected into the three-dimensional frame, and the distances between the sensor system(s) 506 and the various object contact points unprojected into the three-dimensional frame can be determined. In some instances, the unprojected three-dimensional points can correspond to a detailed map representing an environment that has been generated or built up over time using measurements from the sensor system(s) 506 or other mapping software and/or hardware. Because locations of the object contact points are known with respect to a three-dimensional surface, as the object moves over time (and accordingly, as various frames of object contact points are captured over time), various observations about the object such as orientation, length, width, velocity, etc. also can be determined over time. [0083]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique back-projecting one or more values of the sensor data onto the 3D surface topology because such incorporation would help determine distances between the sensor system and the various object contact points. [0083]. Consider claim 5 , Subasingha teaches the processing circuitry further to generate the 3D surface topology of the environment based at least one clipping distance values that exceed a designated maximum distance from the ego-machine in the environment ([0066] – [0070]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique back-projecting one or more values of the sensor data onto the 3D surface topology because such incorporation would help determine distances between the sensor system and the various object contact points. [0083] . 07-21-aia AIA Claim (s) 6 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Henden et al. (US 2026/0017875 A1) and Zhu et al. (US 2022/0292699 A1) . Consider claim 6 , the combnation of Reitmayr and Henden teaches all the limitations in claim 1 but does not explicitly teach the processing circuitry further to compute the 3D surface topology of the environment based at least on a plurality of depth maps representing overlapping view of the environment. Zhu teaches the processing circuitry further to compute the 3D surface topology of the environment based at least on a plurality of depth maps representing overlapping view of the environment ([0065] – [0067], [0118], and claim 31). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of estimate depth data based on a plurality of images because such incorporation would help estimate depth value for each of the missing depth values. [0067]. Consider claim 7 , Zhu teaches the processing circuitry further to detect one or more 3D regions of incomplete content in the 3D surface topology of the environment, and to generate graphical data to replace the one or more detected 3D regions of incomplete content ([0065] – [0070], [0077] – [0084], [0103] – [0106], [0117], [0121] – [0123], [0161]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of estimate depth data based on a plurality of images because such incorporation would help estimate depth value for each of the missing depth values. [0067] . 07-21-aia AIA Claim (s) 3 and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Henden et al. (US 2026/0017875 A1) and Hamilton et al. (US 11,379,950 B1) . Consider claim 3 , Reitmayr teaches all the limitations in claim 1 but does not explicitly teach the processing circuitry further to estimate depth data based at least on two or more images representing a common perspective from different time slices from at least two perspectives, and compute the 3D surface topology based at least on the depth data. Hamilton teaches the processing circuitry further to estimate depth data based at least on two or more images representing a common perspective from different time slices from at least two perspectives (col. 6, line 59 – col. 7, line 21, col. 9, lines 1-25, col. 10, lines 24-51, col. 11, line 35 – col. 12, line 18) , and compute the 3D surface topology based at least on the depth data (col. 10, line 52 – col. 11, line 7). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of estimating depth data based at least on two or more images because such incorporation would enhance accuracy of the existing depth information. Col. 10, lines 24-51. Consider claim 9 , Hamilton teaches the processing circuitry further to warp the sensor data using depth data represented by the 3D surface topology of the environment (col. 7, line 65 – col. 8, line 22, col. 9, lines 25-53, col. 10, line 52 – col. 11, line 2, col. 11, line 56 – col. 12, line 11). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of estimating depth data based at least on two or more images because such incorporation would enhance accuracy of the existing depth information. Col. 10, lines 24-51 . 07-21-aia AIA Claim (s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Henden et al. (US 2026/0017875 A1) and Lin (US 2022/0165031 A1) . Consider claim 8 , Reitmayr teaches all the limitations in claim 1 but does not explicitly teach the processing circuitry further to apply smoothing to the 3D surface topology. Lin teaches the processing circuitry further to apply smoothing to the 3D surface topology ([0097] – [0109], [0127] – [0128], [0170] – [0178]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of smoothing the 3D surface topology because such incorporation would reduce the unevenness on a surface of the 3D mesh. [0098] 07-21-aia AIA Claim (s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Henden et al. (US 2026/0017875 A1) and Wilson et al. (US 2025/0071255 A1) . Consider claim 10 , Reitmayr teaches all the limitations in claim 1 but does not explicitly teach the processing circuitry further to apply a graphical representation for one or more regions of incomplete content in the 3D surface topology based at least on applying blurring. Wilson teaches the processing circuitry further to apply based at least on detecting one or more 3D regions of incomplete content in the 3D surface topology, blurring to a graphical representation corresponding to the one or more 3D regions of incomplete content in the 3D surface topology ([0058] and [0063] – [0064]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of applying a graphical representation for a region of incomplete content in the 3D surface topology based at least on applying blurring because such incorporation would reduce stereo inconsistencies by obscuring or removing the inconsistencies. [0058] . 07-21-aia AIA Claim (s) 12-13 and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Faras et al. (US 2021/0118160 A1) . Consider claim 12 , Reitmayr teaches a system comprising one or more processors to generate a visualization of an environment onto a detected three-dimensional (3D) surface topology of the environment using sensor data generated during one or more sensors of an ego-machine in the environment ([0072] – [0085]). However, Reitmayr does not explicitly teach based at least on projecting one or more color values of image data. Faras teaches based at least on projecting one or more color values of image data (FIG. 2 illustrates image processing of 2D images from a camera to create a 3D image. Referring now to FIG. 2, a camera 100 that is part of a device 202 such as a mobile phone may capture 2D images. Converting 2D images into a 3D representation (also referred to herein as a 3D model) includes multiple, somewhat independent image processing operations, including localization 204 , dense estimation 205 , meshing 206 , and/or texturing 207 . Localization 204 may include 3D map and/or depth determination and pose determination. Pose determination may utilize Simultaneous Localization and Mapping (SLAM), including image-based positioning techniques, to track a location (including position and orientation) of the image capture device in an operating environment. 3D map determination may involve calculation of 3D coordinates or related information (e.g., X, Y, and/or Z coordinates) from a set of 2D images by identifying matching elements in two or more images and triangulating the positions of the matched elements in 3D space. Multiple depth maps can be combined in meshing 206 to create an initial polygon mesh representation of a subject represented in the set of images. Meshing 206 may include sculpting to subdivide surfaces of the initial polygon mesh representation to derive adjusted locations and/or displacements for the vertex positions of some polygons, and storing the adjusted locations and/or displacements in an image map. The values of respective vertices of those polygons may thus be adjusted from their initial value, such that the sculpted model may iteratively define portions with an adjusted topology (representing additional detail) relative to the initial or previous polygon mesh representation. That is, after sculpting, the mesh representation may include vertices whose values have changed from the initial value, and vertices whose values have not changed from the initial value. Texturing and other material application operations may involve applying colors from the original set of images to the 3D mesh representation, for example, by projecting the images onto the mesh and/or segments thereof. Operations for creating a 3D representation, such as those described above, may be collectively referred to herein as 3D scanning. [0036]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of generating a visualization based at least on projecting one or more color values of image data because such incorporation would improve the quality of the 3D map. [0034]. Consider claim 13 , Reitmayr teaches the one or more processors further to represent the detected 3D surface topology of the environment using a 3D signed distance function ([0054] – [0055] and [0074]). Consider claim 18 , Reitmayr teaches the one or more processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D asset; a system for performing deep learning operations; a system for performing real-time streaming; a system for generating or presenting one or more augmented reality content, virtual reality content, or mixed reality content; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for generating synthetic data; a system for generating synthetic data using AI; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources ([0029], [0084]). Consider claim 19 , Reitmayr teaches a method comprising: compute, based at least one image data generated using one or more cameras of an ego-machine in an environment, a three-dimensional (3D) surface topology of the environment ([0072] – [0085]); generate a visualization of an environment onto the 3D surface topology ([0072] – [0085]). However, Reitmayr does not explicitly teach based at least on projecting one or more color values of image data. Faras teaches based at least on projecting one or more color values of image data (FIG. 2 illustrates image processing of 2D images from a camera to create a 3D image. Referring now to FIG. 2, a camera 100 that is part of a device 202 such as a mobile phone may capture 2D images. Converting 2D images into a 3D representation (also referred to herein as a 3D model) includes multiple, somewhat independent image processing operations, including localization 204 , dense estimation 205 , meshing 206 , and/or texturing 207 . Localization 204 may include 3D map and/or depth determination and pose determination. Pose determination may utilize Simultaneous Localization and Mapping (SLAM), including image-based positioning techniques, to track a location (including position and orientation) of the image capture device in an operating environment. 3D map determination may involve calculation of 3D coordinates or related information (e.g., X, Y, and/or Z coordinates) from a set of 2D images by identifying matching elements in two or more images and triangulating the positions of the matched elements in 3D space. Multiple depth maps can be combined in meshing 206 to create an initial polygon mesh representation of a subject represented in the set of images. Meshing 206 may include sculpting to subdivide surfaces of the initial polygon mesh representation to derive adjusted locations and/or displacements for the vertex positions of some polygons, and storing the adjusted locations and/or displacements in an image map. The values of respective vertices of those polygons may thus be adjusted from their initial value, such that the sculpted model may iteratively define portions with an adjusted topology (representing additional detail) relative to the initial or previous polygon mesh representation. That is, after sculpting, the mesh representation may include vertices whose values have changed from the initial value, and vertices whose values have not changed from the initial value. Texturing and other material application operations may involve applying colors from the original set of images to the 3D mesh representation, for example, by projecting the images onto the mesh and/or segments thereof. Operations for creating a 3D representation, such as those described above, may be collectively referred to herein as 3D scanning. [0036]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of generating a visualization based at least on projecting one or more color values of image data because such incorporation would improve the quality of the 3D map. [0034]. Consider claim 20 , Reitmayr teaches the one or more processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D asset; a system for performing deep learning operations; a system for performing real-time streaming; a system for generating or presenting one or more augmented reality content, virtual reality content, or mixed reality content; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for generating synthetic data; a system for generating synthetic data using AI; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources ([0029], [0084]) . 07-21-aia AIA Claim (s) 14-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Faras et al. (US 2021/0118160 A1) and Zhu et al. (US 2022/0292699 A1) . Consider claim 14 , the combnation of Reitmayr and Faras teaches all the limitations in claim 12 but does not explicitly teach the processing circuitry further to compute the detected 3D surface topology of the environment based at least on a plurality of depth maps representing overlapping view of the environment. Zhu teaches the processing circuitry further to compute the detected 3D surface topology of the environment based at least on a plurality of depth maps representing overlapping view of the environment ([0065] – [0067], [0118], and claim 31). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of estimate depth data based on a plurality of images because such incorporation would help estimate depth value for each of the missing depth values. [0067]. Consider claim 15 , Zhu teaches the processing circuitry further to detect one or more 3D regions of incomplete content in the 3D surface topology of the environment, and to generate graphical data to replace the one or more detected 3D regions of incomplete content ([0065] – [0070], [0077] – [0084], [0103] – [0106], [0117], [0121] – [0123], [0161]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of estimate depth data based on a plurality of images because such incorporation would help estimate depth value for each of the missing depth values. [0067] . 07-21-aia AIA Claim (s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Faras et al. (US 2021/0118160 A1) and Hamilton et al. (US 11,379,950 B1) . Consider claim 17 , the combnation of Reitmayr and Faras teaches all the limitations in claim 12 but does not explicitly teach the processing circuitry further to warp the sensor data using depth data represented by the 3D surface topology of the environment. Hamilton teaches the processing circuitry further to warp the sensor data using depth data represented by the 3D surface topology of the environment (col. 7, line 65 – col. 8, line 22, col. 9, lines 25-53, col. 10, line 52 – col. 11, line 2, col. 11, line 56 – col. 12, line 11). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of estimating depth data based at least on two or more images because such incorporation would enhance accuracy of the existing depth information. Col. 10, lines 24-51 . 07-21-aia AIA Claim (s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Reitmayr et al. (US 2022/0122326 A1) in view of Faras et al. (US 2021/0118160 A1) and Lin (US 2022/0165031 A1) . Consider claim 16 , Reitmayr teaches all the limitations in claim 12 but does not explicitly teach the processing circuitry further to apply smoothing to the 3D surface topology. Lin teaches the processing circuitry further to apply smoothing to the 3D surface topology ([0097] – [0109], [0127] – [0128], [0170] – [0178]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the known technique of smoothing the 3D surface topology because such incorporation would reduce the unevenness on a surface of the 3D mesh. [0098]. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAT CHI CHIO whose telephone number is (571)272-9563. The examiner can normally be reached Monday-Thursday 10am-5pm. 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, JAMIE J ATALA can be reached at 571-272-7384. 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. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /TAT C CHIO/ Primary Examiner, Art Unit 2486 Application/Control Number: 18/670,373 Page 2 Art Unit: 2486 Application/Control Number: 18/670,373 Page 3 Art Unit: 2486 Application/Control Number: 18/670,373 Page 4 Art Unit: 2486 Application/Control Number: 18/670,373 Page 5 Art Unit: 2486 Application/Control Number: 18/670,373 Page 6 Art Unit: 2486 Application/Control Number: 18/670,373 Page 7 Art Unit: 2486 Application/Control Number: 18/670,373 Page 8 Art Unit: 2486 Application/Control Number: 18/670,373 Page 9 Art Unit: 2486 Application/Control Number: 18/670,373 Page 10 Art Unit: 2486 Application/Control Number: 18/670,373 Page 12 Art Unit: 2486 Application/Control Number: 18/670,373 Page 13 Art Unit: 2486 Application/Control Number: 18/670,373 Page 14 Art Unit: 2486 Application/Control Number: 18/670,373 Page 15 Art Unit: 2486 Application/Control Number: 18/670,373 Page 16 Art Unit: 2486 Application/Control Number: 18/670,373 Page 17 Art Unit: 2486 Application/Control Number: 18/670,373 Page 18 Art Unit: 2486 Application/Control Number: 18/670,373 Page 19 Art Unit: 2486
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