DETAILED ACTION
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 .
Continued Examination Under 37 CFR 1.114.
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 10/09/2025 has been entered. Claims 1- 20 filed 10/09/2025 are presented for examination.
Response to Arguments
Applicant’s arguments with respect amended claims 1, 2, 10, 11, 13, 16, 17, filed on 10/09/2025 have been considered but they are not persuasive.
The examiner found some limitations are taught by references previous introduced.
In Remark page 10, second paragraph, applicant argued that the cited references at least fail to teach or suggest "obtaining, for a data volume corresponding to a scene to be rendered, information for one or more properties of one or more objects in a plurality of macrocells associated with respective partitions of the data volume, wherein at least one property of the one or more properties comprises a density of at least one object of the one or more objects” and “determining, using a random number generator with a first maximum density of a first macrocell and a second maximum density of a second microcell”.
Examiner respectfully disagrees with Applicant’s argument. In fact, in paragraph [0005], Wald discloses “Once the grid is populated by spatially partitioning the objects into the cells of the grid, each object in the scene corresponds either to a single cell (where the object is bounded by the single cell) or to a group of cells (where the object is bounded by the group of cells)” and [0053] “rendering three-dimensional images and scenes using processing functions that act upon 3D primitive shapes” and [0224] “in the context of volume rendering, a given volume data set 2200 is too large to be rendered on one node, so it gets partitioned into multiple blocks 2201-2204 (in this case, a 2×2 set)” and [0226] “FIG.25, each node computes what is commonly known as a “macrocell grid”; a lower resolution grid where each cell corresponds to a region of cells in the input volume” and Fig. 29, [0230] “At 2901, a volume is logically subdivided into a plurality of partitions (N) and, at 2902, data associated with the N partitions is distributed to N different nodes” Wald teaches, each object in the scene, obtaining, for a data volume (the input volume data set is too large), one or more properties of an object corresponding to either a single cell or a group of cells. A density information for a plurality of macrocells (referred to as a group of cells) associated with respective partitions of the data volume of the objects into the cells of the grid, e.g., density is referred to a number N macrocells (nodes) associated with respective partitions of the data volume. Furthermore, a volume subdivision module to subdivide a volume into a plurality of partitions, the apparatus to process a first of the partitions and to distribute data associated with each of the other partitions to each of a plurality of nodes (abstract) as a grid (Figs. 22, 26, 28), the structured grid might be used such that a given volume is always partitioned into a fixed number of partitions (N partitions), or macrocells.
In additional, in abstract, Wald discloses “a proxy generation module to compute a first proxy for the first partition, the first proxy to be transmitted to the plurality of nodes” and [0226] “each node 2010-2013 computes a local proxy 2040-2043 for its part of the data 2201-2204, respectively, where the proxy is any sort of object that is (significantly) smaller in size…where each such cell stores, for example, the minimum and maximum scalar value in that region (in the context of single-node rendering…each node 2010-2013 computes one such proxy 2040-2043 for its part of the data, all nodes then exchange their respective proxies until each node has all proxies for every node, as illustrated in FIG. 26” and [0228] “In addition, since every node has every other nodes' proxies each node can also conservatively bound which other nodes' regions are interesting based on the proxies it has for these nodes, as shown in FIG. 28. If node 2010 has to trace a ray that straddles node's 2011-2013's data regions then the ray may be projected onto the proxy and traversed there, as indicated by the dotted arrow” Wald teaches determining, using a random number generator (e.g., a proxy generation module randomly computes proxy/small item in size, proxy 2040-2043 for its part of the data, all nodes then exchange their respective proxies until each node 2010-2013 has all proxies for every node) with a first maximum density (proxies) of a first macrocell (node 2010, Fig. 28) and a second maximum density (proxies) of a second microcell (node 2011, Fig. 28);
In Remark page 12, last line, page 13, first line applicant argued that “Finally, Ozdas is silent on "determin[ing] sample locations for the light ray in the first microcell and the second macrocell."
Examiner respectfully disagrees with Applicant’s argument. In fact, in paragraph [0004], Ozdas discloses “An area of the conic section being marched is determined based on a spreading factor and a distance from the point in the 3-D scene to a current sampling point. Light energy data is collected from the volume elements intersected by the conic section during the marching” and [0049] “FIG. 6 depicts a cross-section 142 of the conic projection discussed with respect to FIG. 5. In FIG. 6, the volume elements are of size like that of volume element 127. FIG. 6 thus depicts that some volume elements are entirely within the area of cross-section 142” and [0044] “The location can be a point on a surface of an object in a scene, or a sample of a pixel in a rendering, for example. At 267, a ray (ray 124 of FIG. 5) is defined to be emitted from proximate the point, in a direction, and is associated with a spreading factor. In FIG. 5, an expression of the spreading factor is depicted (in 2-D) as a cone defined by boundaries 125 and 126 that bracket ray 124. At 269, a transition zone is defined and includes maximum and minimum ray tracing distances (minimum distance 131 and maximum distance 132 of FIG. 5)” Ozdas teaches step sizes (define a ray tracing distance, step 269) to be used to determine sample locations for the first light ray (124) in the first macrocell (the cell is intercepted with the light ray with distance 131, Fig. 5) and the second microcell (the cell is intercepted with the light ray with distance 132, Fig. 5).
In Remark page 13, fourth paragraph, applicant argued that “Wrenninge is silent on using a random number generator to generate "one or more random distances for the light ray to travel."
Examiner respectfully disagrees with Applicant’s argument. In fact, in Col 8, lines 9-15, Wrenninge discloses “voxel arrays 502-510 may store parameter values corresponding to a time range, voxel buffer 500 includes arrays with up to six time steps in the range t=0 to t=1, it will be recognized that other numbers of time steps may be used” and Fig. 12, Col. 14 lines 14-18 “At operation 1210, ray marching is performed for current ray r, the value of a parameter may be obtained for each voxel along the path ray r takes through voxel grid 300 at the time associated with ray r at the time associated with time r” and Col. 13 lines 42-50 “A plurality of rays 1100-1104 are cast through voxel grid 300 to arrive at pixel 1110. Ray 1100 may be defined by the location of a pixel of an image to be rendered, and the point at which the ray enters voxel grid 300, example of FIG. 11, ray 1102 is cast at time t=0.2 in a first direction, ray 1104 is cast at time t=1.0 in a second direction, and ray 1106 is cast at time t=0.5 in a third direction. The direction of each ray 1100 and the time associated with each ray 1100 may be determined randomly, pseudorandomly“ and Fig. 12, Col. 13 lines 63-67, Col. 14, line 1 “At operation 1206, multiple sample times and multiple sample position (e.g., N sample times and N sample positions of entry into a voxel grid) are determined for pixel p. The N sample times and N sample positions may be determined, for example, using a random or pseudorandom process, such as a random number generator” Wrenninge teaches random distances for the one or more step sizes (the steps size of the length of time t, in the time range) along for the first light ray travels (rays 1102 (first light ray), 1104,1106, Fig. 11) to sample positions for pixel p (the point at which the ray enter voxel grid 300) are generated by a pseudorandom process, such as a random number generator.
Independent claims 10, 16 are included some of those discussed above in connection with claim 1 and are rejected as above explanation.
Claims 2, 5, 6, 8, 9, 11, 14, 15, 17, 19, and 20 depend from independent claims 1, 10, 16 and the rejections to the claims are maintained.
Claim Rejections - 35 USC § 103
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 of this title, 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 1-2, 5-6, 8-11, 14-17 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable by Wald (U.S. 2022/0012935 A1) in view of Ozdas et al.(U.S. 2024/0233243 A1) and further in view of Wrernninge (U.S. 9,292,953 B1).
Regarding Claim 1 (Currently amended), Wald discloses a computer-implemented method (Wald, [0001] “method for data-parallel ray tracing using volume proxies”), comprising:
obtaining, for a data volume corresponding to a scene to be rendered, density information for one or more objects in a plurality of macrocells associated with respective partitions of the data volume, wherein at least one property of the one or more properties comprises a density of at least one object of the one or more objects (Wald, [0005] “Once the grid is populated by spatially partitioning the objects into the cells of the grid, each object in the scene corresponds either to a single cell (where the object is bounded by the single cell) or to a group of cells (where the object is bounded by the group of cells)” and [0053] “rendering three-dimensional images and scenes using processing functions that act upon 3D primitive shapes” and [0224] “in the context of volume rendering, a given volume data set 2200 is too large to be rendered on one node, so it gets partitioned into multiple blocks 2201-2204 (in this case, a 2×2 set)” and [0226] “FIG.25, each node computes what is commonly known as a “macrocell grid”; a lower resolution grid where each cell corresponds to a region of cells in the input volume” and Fig. 29, [0230] “At 2901, a volume is logically subdivided into a plurality of partitions (N) and, at 2902, data associated with the N partitions is distributed to N different nodes” Wald teaches, obtaining, for a data volume (the input volume data set is too large), one or more properties of an object corresponding to either a single cell or a group of cells. A density information for a plurality of macrocells (referred to as a group of cells) associated with respective partitions of the data volume of the objects into the cells of the grid, e.g., density is referred to a number N macrocells (nodes) associated with respective partitions of the data volume.
Furthermore, a volume subdivision module to subdivide a volume into a plurality of partitions, the apparatus to process a first of the partitions and to distribute data associated with each of the other partitions to each of a plurality of nodes (abstract) as a grid (Figs. 22, 26, 28), the structured grid might be used such that a given volume is always partitioned into a fixed number of partitions (N partitions), or macrocells.
selecting a first light ray to be traced through the plurality of macrocells (Wald, [0225] Traditionally, every time a node wants to send a ray that passes through other nodes' spatial regions, it has to either send this ray to those nodes, or fetch those nodes' data. In FIG. 24, node 2010 traces a ray that passes through space owned by nodes 2011-2013” Wald teaches selecting a first light ray to be traced through macrocells (nodes 2010-2013);
determining, using a random number generator with a first maximum density of a first macrocell and a second maximum density of a second microcell (Wald, abstract “a proxy generation module to compute a first proxy for the first partition, the first proxy to be transmitted to the plurality of nodes” and [0226] “each node 2010-2013 computes a local proxy 2040-2043 for its part of the data 2201-2204, respectively, where the proxy is any sort of object that is (significantly) smaller in size…where each such cell stores, for example, the minimum and maximum scalar value in that region (in the context of single-node rendering…each node 2010-2013 computes one such proxy 2040-2043 for its part of the data, all nodes then exchange their respective proxies until each node has all proxies for every node, as illustrated in FIG. 26” and [0228] “In addition, since every node has every other nodes' proxies each node can also conservatively bound which other nodes' regions are interesting based on the proxies it has for these nodes, as shown in FIG. 28. If node 2010 has to trace a ray that straddles node's 2011-2013's data regions then the ray may be projected onto the proxy and traversed there, as indicated by the dotted arrow” Wald teaches determining, using a random number generator (e.g., a proxy generation module randomly computes proxy/small item in size, proxy 2040-2043 for its part of the data, all nodes then exchange their respective proxies until each node 2010-2013 has all proxies for every node) with a first maximum density (proxies) of a first macrocell (node 2010, Fig. 28) and a second maximum density (proxies) of a second microcell (node 2011, Fig. 28);
forwarding information for the first light ray from the first macrocell to a third macrocell through which the first light ray is to be traced, without forwarding the information for the first light ray to the second macrocell, wherein volume sampling will be performed for the first light ray in the third macrocell but not the second macrocell, and wherein the third macrocell is adjacent to or distant from the second microcell (Wald, [0028] “as shown in FIG. 28. If node 2010 has to trace a ray that straddles node's 2011-2013's data regions then the ray may be projected onto the proxy and traversed there, as indicated by the dotted arrow. This indicates that though the ray does pass through space owned by nodes 2010-1212, only node 2012 actually contains any interesting regions, so this ray can be forwarded to node 2012, as indicated in FIG. 28 by the solid arrow, without processing on nodes 2010 or sending to node 2011 (or, in a caching context, data may be fetched only from node 2010 rather than from both 2011 and 2012) Wald teaches forwarding information for the first light ray from 1st macrocell (node 2010) to a 3rd macrocell (node 2012) (Fig. 28) without forwarding information to the 2nd microcell (node 2011), 2nd marcocell (node 2011) is adjacent to the 3rd marcrocell (node 2012).
However, Wald does not explicitly teach one or more step sizes to be used to determine a plurality of sample locations along [[for]] the first light ray in the first macrocell and the second microcell, wherein the random number generator generates one or more random distances for the one or more step sizes along [[for]] the first light ray to travel;
determining that none of the sample locations are located within the second macrocell; and
Ozdas teaches one or more step sizes to be used to determine a plurality of sample locations along the first light ray in the first macrocell and the second macrocell (Ozdas, [0004] “An area of the conic section being marched is determined based on a spreading factor and a distance from the point in the 3-D scene to a current sampling point. Light energy data is collected from the volume elements intersected by the conic section during the marching” and [0049] “FIG. 6 depicts a cross-section 142 of the conic projection discussed with respect to FIG. 5. In FIG. 6, the volume elements are of size like that of volume element 127. FIG. 6 thus depicts that some volume elements are entirely within the area of cross-section 142” and [0044] “The location can be a point on a surface of an object in a scene, or a sample of a pixel in a rendering, for example. At 267, a ray (ray 124 of FIG. 5) is defined to be emitted from proximate the point, in a direction, and is associated with a spreading factor. In FIG. 5, an expression of the spreading factor is depicted (in 2-D) as a cone defined by boundaries 125 and 126 that bracket ray 124. At 269, a transition zone is defined and includes maximum and minimum ray tracing distances (minimum distance 131 and maximum distance 132 of FIG. 5)” Ozdas teaches step sizes (define a ray tracing distance, step 269) to be used to determine sample locations for the first light ray (124) in the first macrocell (the cell is intercepted with the light ray with distance 131) and the second microcell (the cell is intercepted with the light ray with distance 132) (Fig. 5).
determining that none of the sample locations are located within the second macrocell (Ozdas, [0035] In FIG. 3, volume elements 50-52 are specifically identified. Volume elements are associated with light transport characterization data. Light transport characterization data for a given volume element characterizes transport of light energy from that element; such light energy may be generated in that volume element” Ozdas teaches determine that none of the sample locations are located within the second macrocell, e.g., the element is located between the element 50 and the element 51 and this element does not contain any primitive/shape or light, it is empty, see Fig. 3);
Wald and Ozdas are combinable because they are from the same field of endeavor, system and method for image processing and try to solve similar problems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made for modifying the method of Wald to combine with step size for the light ray in the first macrocell and the second macrocell (as taught Ozdas) in order to provide step sizes to be used to determine sample locations for the light ray in the first macrocell and the second macrocell because Ozdas can provide step sizes (define a ray tracing distance, step 269) to be used to determine sample locations for the first light ray (124) in the first macrocell (the cell is intercepted with the light ray with distance 131) and the second microcell (the cell is intercepted with the light ray with distance 132) (Fig. 5). (Ozdas, Figs 5, 6, [0004], [0049]). Doing so, it may provide keeping the sampling density relatively low allows lower computation cost for ray tracing (Ozdas, [0024]).
Wrenninge teaches the random number generator generates one or more random distances for the one or more step sizes along the first light ray to travel (Wrenninge, Col 8, lines 9-15 “voxel arrays 502-510 may store parameter values corresponding to a time range, voxel buffer 500 includes arrays with up to six time steps in the range t=0 to t=1, it will be recognized that other numbers of time steps may be used” and Fig. 12, Col. 14 lines 14-18 “At operation 1210, ray marching is performed for current ray r, the value of a parameter may be obtained for each voxel along the path ray r takes through voxel grid 300 at the time associated with ray r at the time associated with time r” and Col. 13 lines 42-50 “A plurality of rays 1100-1104 are cast through voxel grid 300 to arrive at pixel 1110. Ray 1100 may be defined by the location of a pixel of an image to be rendered, and the point at which the ray enters voxel grid 300, example of FIG. 11, ray 1102 is cast at time t=0.2 in a first direction, ray 1104 is cast at time t=1.0 in a second direction, and ray 1106 is cast at time t=0.5 in a third direction. The direction of each ray 1100 and the time associated with each ray 1100 may be determined randomly, pseudorandomly“ and Fig. 12, Col. 13 lines 63-67, Col. 14, line 1 “At operation 1206, multiple sample times and multiple sample position (e.g., N sample times and N sample positions of entry into a voxel grid) are determined for pixel p. The N sample times and N sample positions may be determined, for example, using a random or pseudorandom process, such as a random number generator” Wrenninge teaches random distances for the one or more step sizes (the steps size of the length of time t, in the time range) along for the first light ray travels (rays 1102 (first light ray), 1104,1106, Fig. 11) to sample positions for pixel p (the point at which the ray enter voxel grid 300) are generated by a pseudorandom process, such as a random number generator.
Furthermore, Wrenninge also discloses the density information can be used select these sample locations, (Wrenninge, Fig. 4A, Col. 3, line 67, Col. 4, lines 1-4 “Parameter values such as density, can be sampled at multiple times and multiple positions within the voxel grid (e.g., random times and random positions are referred to as the density information)” and can be combined with Wald to teach more the limitation “density information” of claim 1.
Wald, Ozdas and Wrenninge are combinable because they are from the same field of endeavor, system and method for image processing and try to solve similar problems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made for modifying the method of Wald to combine with (as taught Wrenninge) in order to apply the random number generator generates one or more random distances for the light ray to travel because Wrenninge can provide random distances to sample positions (the point at which the ray enter voxel grid 300) for the light ray travel (rays 1102, 1104,1106, Fig. 11) are generated by a pseudorandom process, such as a random number generator (Wrenninge, Fig. 11m Col. 13 lines 43-50, Fig. 12, Col. 13 lines 63-67, Col. 14, line 1). Doing so, it may provide when sampling values along rays through the lattice, a motion blur effect results from sampling randomly in time (Wrenninge, Col. 1, lines 28-29).
Regarding Claim 2 (Currently amended), a combination of Wald, Ozdas and Wrenninge discloses the computer-implemented method of claim 1, wherein the information for the first light ray is forwarded to the third macrocell after determining that the first light ray will be sampled in the third macrocell (Wald, [0032] FIG. 28, in which one particular node includes relevant data for a particular ray” and [0228] “as shown in FIG. 28. If node 2010 has to trace a ray that straddles node's 2011-2013's data regions then the ray may be projected onto the proxy and traversed there, as indicated by the dotted arrow This indicates that though the ray does pass through space owned by nodes 2010-1212, only node 2012 actually contains any interesting regions, so this ray can be forwarded to node 2012, as indicated in FIG. 28 by the solid arrow” Wald teaches the information for the first light ray (solid arrow) is forwarded to the third microcell (node 2012) after determining that the first light ray will be sampled in the third microcell (Fig. 28).
Regarding Claim 5, the computer-implemented method of claim 1, Wald discloses does not explicitly teach wherein the individual macrocells further include a plurality of cells associated with points in the data volume.
However, Ozdas teaches wherein the individual macrocells further include a plurality of cells associated with points in the data volume (Ozdas, [0031] “examples of using both point sampling and volume sampling techniques (e.g., ray tracing and volume element sampling) in order to determine lighting information at a location in a 3-D scene are disclosed. In summary of the following, point sampling is undertaken for one or more samples that are limited to within a threshold distance of the point” and [0066] “FIG. 14 depicts an example of light energy records located within defined volume elements of a 3-D space…Light energy record 496 includes data defining an emission 497 that has a directionally-specific distribution of light energy” Ozdas teaches individual macrocells (a volume element) associated with points in the data volume (Fig. 14).
Wald and Ozdas are combinable see rationale in claim 1.
Regarding Claim 6, a combination of Wald, Ozdas and Wrenninge discloses the computer-implemented method of claim 1, wherein the data volume is a structured data volume or an unstructured data volume (Wald, [0021] “in volume rendering the user often uses a “transfer function” to highlight certain regions of the data. Similarly, for surface-based ray tracing, if a ray passes through a region of space owned by another node” and [0201] “the selection of between GPU bias and host processor bias is driven by a bias tracker data structure” Wald teaches the data volume is a structured data volume.
Regarding Claim 8, a combination of Wald, Ozdas and Wrenninge discloses the computer-implemented method of claim 1, wherein the data volume is associated with an acceleration structure to be used to calculate the first maximum density and the second maximum density (Wald, [0054] “media pipeline 316 includes fixed function or programmable logic units to perform one or more specialized media operations, such as video decode acceleration, video de-interlacing, and video encode acceleration in place of, or on behalf of video codec engine 306” and [0226] “each node computes what is commonly known as a “macrocell grid”; a lower resolution grid where each cell corresponds to a region of cells in the input volume, and where each such cell stores, for example, the minimum and maximum scalar value in that region (in the context of single-node rendering,) Wald teaches the data volume is associated with an acceleration structure (e.g., decode acceleration, encode acceleration) to be used to calculate the first maximum density and the second maximum density.
Regarding Claim 9 (Currently amended), a combination of Wald, Ozdas and Wrenninge discloses the computer-implemented method of claim 1, wherein a first sample location along [[for]] the first light ray is determined to be in the third macrocell, and wherein the tracing of the ray is allowed to begin from the third macrocell (Wald, [0032] “FIG. 28 illustrates one embodiment of the invention in which one particular node includes relevant data for a particular ray” and [0228] “This indicates that though the ray does pass through space owned by nodes 2010-1212, only node 2012 actually contains any interesting regions, so this ray can be forwarded to node 2012, as indicated in FIG. 28 by the solid arrow, without processing on nodes 2010” Wald teaches the 1st sample location for the first light ray is determined to be in the third microcell (node 2012) and wherein the tracing of the ray is allowed to begin from the third microcell (Fig. 28).
Regarding Claim 10 (Currently amended), a combination of Wald, Ozdas and Wrenninge, discloses a processor (Wald, [0035] “one or more processors 102”), comprising:
one or more circuits (Wald, [0049] “one or more chips or as an SoC integrated circuit having the illustrated components”) to:
obtain, for a data volume corresponding to a scene to be rendered, density information for one or more objects in each of a plurality of macrocells corresponding to partitions of the data volume;
select a first light ray to be traced through the plurality of macrocells;
determine, using random numbers with a first maximum density of a first macrocell and a second maximum density of a second macrocell, a plurality of step sizes to be used for sampling the first light ray in the first macrocell and the second macrocell, wherein the random number generator generates one or more random distances for the plurality of step size along the first light ray ;
determine, based at least in part upon the one or more step sizes, that the first light ray will pass from the first macrocell without being sampled in the second macrocell; and
forward information for the light ray to processor for a third macrocell through which the first light ray is to be traced, without forwarding the information for the first light ray to a processor associated with the second macrocell, wherein volume sampling will not be performed for the first light ray using the processor for the second macrocell and wherein the third macrocell is adjacent to or distant from the second macrocell in the data volume.
Claim 10 is substantially similar to claim 1 is rejected based on similar analyses.
Regarding Claim 11 (Currently amended), a combination of Wald, Ozdas and Wrenninge discloses the processor of claim 10, wherein the information for the first light ray is forwarded to the third macrocell after determining that the first light ray will be sampled in the third macrocell.
Claim 11 is substantially similar to claim 2 is rejected based on similar analyses.
Regarding Claim 14, a combination of Wald, Ozdas and Wrenninge, discloses the processor of claim 10, wherein one or more individual macrocells further include a plurality of cells associated with points in the data volume.
Claim 14 is substantially similar to claim 5 is rejected based on similar analyses.
Regarding Claim 15, a combination of Wald, Ozdas and Wrenninge, discloses the processor of claim 10, wherein the processor is comprised in at least one of:
a system for performing simulation operations, (Wald, [0115] “FIG. 11 A design facility 1130 can generate a software simulation 1110 of an IP core design in a high level programming language (e.g., C/C++). The software simulation 1110 can be used to design, test, and verify the behavior of the IP core using a simulation model 1112. The simulation model 1112 may include functional, behavioral, and/or timing simulations” Wald teaches a system for performing simulation operations;
a system for performing simulation operations to test or validate autonomous machine applications;
a system for performing digital twin operations;
a system for performing light transport simulation;
a system for rendering graphical output;
a system for performing deep learning operations;
a system implemented using an edge device;
a system for generating or presenting virtual reality (VR) content;
a system for generating or presenting augmented reality (AR) content;
a system for generating or presenting mixed reality (MR) content;
a system incorporating one or more Virtual Machines (VMs);
a system implemented at least partially in a data center; a system for performing hardware testing using simulation;
a system for performing generative operations using a language model;
a system for synthetic data generation;
a system for performing generative AI operations using a large language model (LLM),
a collaborative content creation platform for 3D assets; or
a system implemented at least partially using cloud computing resources.
Regarding Claim 16 (Currently amended), a combination of Wald, Ozdas and Wrenninge, discloses a system (Wald, [0035] “a processing system 100”), comprising:
one or more processing units (Wald, [0035] “one or more processors 102”) to use a random number generator and maximum density values, for one or more density values of at least one object of one or more objects in a plurality of macrocells for a scene to be rendered (Wald, [0005] “Once the grid is populated by spatially partitioning the objects into the cells of the grid, each object in the scene corresponds either to a single cell (where the object is bounded by the single cell) or to a group of cells (where the object is bounded by the group of cells)” and [0224] “in the context of volume rendering, a given volume data set 2200 is too large to be rendered on one node, so it gets partitioned into multiple blocks 2201-2204 (in this case, a 2×2 set)” Wald teaches plurality of multiple macrocells (referred to as the partitioned blocks) are rendered with maximum density values (multiple 2x2 sets) of objects into group of cells.
However, Wald does not explicitly teach determine, based on generated random numbers, a plurality of step sizes to be used for a first light ray to be traced through the plurality of macrocells, the a plurality of step sizes to be used to determine one or more macrocells to which to forward information for the light ray based, at least in part, upon a determination of a first light sampling being performed in the one or more macrocells at sample locations along the first light ray corresponding to the a plurality of step sizes.
Ozdas teaches determine, based on generated random numbers, a plurality of step sizes to be used for a first light ray to be traced through the plurality of macrocells, the a plurality of step sizes to be used to determine one or more macrocells to which to forward information for the first light ray based, at least in part, upon a determination of a first light sampling being performed in the one or more macrocells at sample locations along the first light ray corresponding to the a plurality of step sizes (Ozdas, [0031] “using both point sampling and volume sampling techniques (e.g., ray tracing and volume element sampling) in order to determine lighting information at a location in a 3-D scene are disclosed… volume sampling is undertaken by marching a conic section through a grid of volume elements. Sizes of the volume elements sampled can be determined according to distance from the point” and [0035] “In FIG. 3, volume elements 50-52 are specifically identified. Volume elements are associated with light transport characterization data” and [0044] “The location can be a point on a surface of an object in a scene, or a sample of a pixel in a rendering, for example. At 267, a ray (ray 124 of FIG. 5) is defined to be emitted from proximate the point, in a direction, and is associated with a spreading factor. In FIG. 5, an expression of the spreading factor is depicted (in 2-D) as a cone defined by boundaries 125 and 126 that bracket ray 124. At 269, a transition zone is defined and includes maximum and minimum ray tracing distances (minimum distance 131 and maximum distance 132 of FIG. 5)” Ozdas teaches a plurality of step sizes (define a ray tracing distance, step 269, Fig. 9) to be used to determine sample locations for the first light ray (124) in the first macrocell (the cell is intercepted with the light ray with distance 131) and the second macrocell (the cell is intercepted with the light ray with distance 132) (Fig. 5) (the first light ray performed in one or more macrocells).
Wald and Ozdas are combinable see rationale in claim 1.
Wrenninge teaches determine, based on generated random numbers, step sizes to be used for a light ray to be traced through the plurality of macrocells (Wrenninge, Col. 13 lines 43-50 “Ray 1100 may be defined by the location of a pixel of an image to be rendered, and the point at which the ray enters voxel grid 300, example of FIG. 11, ray 1102 is cast at time t=0.2 in a first direction, ray 1104 is cast at time t=1.0 in a second direction, and ray 1106 is cast at time t=0.5 in a third direction. The direction of each ray 1100 and the time associated with each ray 1100 may be determined randomly, pseudorandomly“ and Fig. 12, Col. 13 lines 63-67, Col. 14, line 1 “At operation 1206, multiple sample times and multiple sample position (e.g., N sample times and N sample positions of entry into a voxel grid) are determined for pixel p. The N sample times and N sample positions may be determined, for example, using a random or pseudorandom process, such as a random number generator” Wrenninge teaches a step sizes (the operation 1206, Fig. 12) for the light ray travel (rays 1102, 1104,1106, Fig. 11) are generated by a pseudorandom process, such as a random number generator to sample positions through macrocells (referred to as the ray enter plurality cells of a voxel grid 300).
Wald, Ozdas and Wrenninge are combinable see rationale in claim 1.
Regarding Claim 17 (Currently amended), a combination of Wald, Ozdas and Wrenninge, discloses the system of claim 16, wherein the information for the first light ray is forwarded to a subsequent macrocell the third microcell after determining that the first light ray is to be sampled in the subsequent macrocell third macrocell.
Claim 17 is substantially similar to claim 2 is rejected based on similar analyses.
Regarding Claim 19, a combination of Wald, Ozdas and Wrenninge, discloses the system of claim 16, wherein one or more individual macrocells further include a plurality of cells associated with points in the data volume.
Claim 19 is substantially similar to claim 5 is rejected based on similar analyses.
Regarding Claim 20, a combination of Wald, Ozdas and Wrenninge, discloses the system of claim 16, wherein the system comprises at least one of:
a system for performing simulation operations;
a system for performing simulation operations to test or validate autonomous machine applications;
a system for performing digital twin operations;
a system for performing light transport simulation;
a system for rendering graphical output;
a system for performing deep learning operations;
a system for performing generative AI operations using a large language model (LLM),
a system implemented using an edge device;
a system for generating or presenting virtual reality (VR) content;
a system for generating or presenting augmented reality (AR) content;
a system for generating or presenting mixed reality (MR) content;
a system incorporating one or more Virtual Machines (VMs);
a system implemented at least partially in a data center;
a system for performing hardware testing using simulation;
a system for performing generative operations using a language model;
a system for synthetic data generation;
a collaborative content creation platform for 3D assets; or
a system implemented at least partially using cloud computing resources.
Claim 20 is substantially similar to claim 15 is rejected based on similar analyses.
Claims 4 and 13 are rejected under 35 U.S.C. 103 as being unpatentable by Wald (U.S. 2022/0012935 A1) in view of Ozdas et al.(U.S. 2024/0233243 A1) and further in view of Wrernninge (U.S. 9,292,953 B1) and further in view of Loffler et al.(U.S. 2019/0272027 A1).
Regarding Claim 4, the computer-implemented method of claim 1, a combination of Wald, Ozdas and Wrenninge does not explicitly teach wherein the one or more step sizes correspond to one or more Woodcock step sizes.
However, Loffer teaches wherein the one or more step sizes correspond to one or more Woodcock step sizes (Loffer, [0070] “An alternative Monte Carlo algorithm especially for volume rendering can be based on Woodcock Tracking. Woodcock tracking propagates through the volume with random step length and determinates a single scattering point” Loffer a step size (step length) corresponding to Woodcock tracking for volume rendering.
Wald, Ozdas, Wrernninge and Loffer are combinable because they are from the same field of endeavor, system and method for image processing and try to solve similar problems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made for modifying the method of Wald to combine with step sizes corresponding to Woodcock step (as taught by Loffer) in order to provide step sizes, correspond to one or more Woodcock step sizes because Loffer can provide a step size (step length) corresponding to Woodcock tracking for volume rendering (Loffer, [0070]). Doing so, it may provide an adaptive rendering provides the virtual reality user with highest quality images without negative motion related effects due to slow rendering performance (Loffer, [0004]).
Regarding Claim 13 (Currently amended), a combination of Wald, Ozdas, Wrenninge and Loffer discloses the processor of claim 10, wherein the plurality of step sizes corresponds to one or more Woodcock step sizes.
Claim 13 is substantially similar to claim 4 is rejected based on similar analyses.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable by Wald (U.S. 2022/0012935 A1) in view of Ozdas et al.(U.S. 2024/0233243 A1) and further in view of Wrernninge (U.S. 9,292,953 B1) and further in view of Khorasani et al.( U.S.9,855,894 B1).
Regarding Claim 7, the computer-implemented method of claim 1, a combination of Wald, Ozdas and Wrenninge does not explicitly teach wherein the one or more step sizes are sampled from an exponential distribution.
However, Khorasani teaches the one or more step sizes are sampled from an exponential distribution (Khorasani, Col. 13, L 48-53 “The outputs of modules 602-604 and 608-610 may be provided to raymarching module 608 that performs a volume ray casting using a form of ray tracing in which imaginary light ray are computed where they intersect with solid parts of an object and are also sampled and modified as they pass through space” and Col. L 58-61 “where frustum to cuboid direct mapping may be performed using normalized coordinates (e.g., width×height axis), where exponential depth distribution may be performed for depth slices” Khorasani teaches step sizes (e.g., width×height axis) are sampled from an exponential depth distribution.
Wald, Ozdas, Wrernninge and Khorasani are combinable because they are from the same field of endeavor, system and method for image processing and try to solve similar problems. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made for modifying the method of Wald to combine with step sizes are sampled from an exponential distribution (as taught by Khorasani) in order to provide because Khorasani can provide step sizes (e.g., width×height axis) are sampled from an exponential depth distribution (Khorasani, Col. 13, L 48-53, Col. L 58-61). Doing so, it may process the sensor confidence value to modify the scene on the display to represent the estimated accuracy for the at least one or more of the sensors (Khorasani, Col. 1, L 67, Col. 2, L 1-2).
Allowable Subject Matter
Dependent claims 3, 12,18 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.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding to dependent claims 3,12,18, the closest prior art references the examiner found are Wald (U.S. 2022/0012935 A1) in view of Ozdas et al.(U.S. 2024/0233243 A1) and Wrernninge (U.S. 9,292,953 B1) have been made of record as teaching: obtaining, for a data volume corresponding to a scene to be rendered, density information for a plurality of macrocells associated with respective partitions of the data volume (Wald, [0053], [0224], [0226]); selecting a light ray to be traced through the plurality of macrocells (Wald, [0225]); one or more step sizes to be used to determine sample locations for the light ray in the first macrocell and the second macrocell (Ozdas, [0031], [0035], [0066]); determining that none of the sample locations are located within the second macrocell (Ozdas, [0035]); the random number generator generates one or more random distances for the light ray to travel (Wrenninge, Fig. 11, Col. 13 lines 43-50) recited in claims 1, 10, 16.
However, the art of record did not teach or suggest the claim taken as a whole and particular the limitation pertaining
“determining an actual density value corresponding to a first step size; and rejecting a sample value corresponding to the first step size if the actual density value is more than a threshold amount lower than the maximum density for the first macrocell” recited in dependent claims 3, 12,18.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance”.
Conclusion
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/KEE M TUNG/Supervisory Patent Examiner, Art Unit 2611
/KHOA VU/Examiner, Art Unit 2611