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 Objections
Claims 29-33 are objected to because of the following informalities: Claims 29-33 recite "the method according to claim 28" or "the method according to claim 29." Claims 29-33 are dependent upon claim 28 where claim 28 is directed to a non-transitory computer-readable storage medium. As such, dependent claims 29-33 should also be directed to a non-transitory computer-readable storage medium, not a method. Appropriate correction is required.
Response to Amendment
The amendment filed March 19th, 2026 has been entered. Claims 1-6, 9, and new claims 21-33 are pending in the application. The applicant’s amendments to the claims have overcome all claim objections and rejections under 35 USC 112(b) previously set forth in the Non-Final Office Action of December 19th, 2025.
Response to Arguments
Applicant's arguments filed March 19th, 2026 have been fully considered but they are not persuasive.
Applicant states:
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Remarks, pages 8-9
The examiner disagrees because Sugio’s NumNeighborPoint and mesh_position_prediction_max_parallelograms_minus1 are functional equivalents. Therefore, considering broadest reasonable interpretation, Sugio’s NumNeighborPoint reads on mesh_position_prediction_max_parallelograms_minus1 syntax.
Further applicant states:
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The examiner disagrees because by limiting the number of predictors / prediction candidates, the processing amount is reduced. Limited predictors/ prediction candidates enables fewer calculations, limits resource consumption, and enables faster, deterministic calculation times.
In response to applicant's argument that " even if those features cited by the rejection would reduce processing in Sugio, the other references were not shown to have such features in the first place and so the combination would not obviously 'reduce the processing amount'", the test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981).
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, 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 1-3, 5, 21-23, 25, and 28-31 are rejected under 35 U.S.C. 103 as being unpatentable over Kondrad (WO 2023052916 A1) in view of Chen (US 8884953 B2) in further view of Sugio (US 20230222698 A1).
Regarding claim 1 Kondrad teaches a method for video decoding, the method performed by at least one processor (“A still another example apparatus includes at least one processor; and at least one non- transitory memory comprising computer program code; wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform: receive a bitstream comprising one or more vertices of a mesh, wherein the one or more vertices are stored by using an extension to a volumetric video coding structure; wherein the extension to the volumetric coding structure enables storage of information corresponding to an algorithm for compression of a mesh; and decode the bitstream," (Kondrad, para [0139])) and comprising:
obtaining, from a bitstream, a mesh representing an encoded volumetric data of at least one three-dimensional (3D) visual content ((Kondrad, para [0139]). Volumetric video is mapped to three-dimensional (3D) visual content because a volumetric video captures a three-dimensional space, (Kondrad, para [0022]). The vertex is mapped to encoded volumetric data, (Kondrad, para [0022]).);
Kondrad does not explicitly teach but Chen teaches partitioning a plurality of vertices of the mesh into a plurality of groups, at least one of the groups representing a shape of a parallelogram (“the prediction triangle can be generated by constructing an auxiliary triangle as a parallelogram extension of the reference triangle" (col 4, lines 38-56). The auxiliary triangle as a parallelogram extension of the reference triangle reads on a group representing the shape of a parallelogram. The prediction triangle and auxiliary triangle as a parallelogram extension of the reference triangle comprise more than one group, and thus reads on a plurality of groups. The triangles are partitioned vertices since the triangles comprise vertices (abstract, lines 1-4)); and
decoding the encoded volumetric data by predicting the vertices in each group of the plurality of groups based on a prediction mode associated with said each group ("The geometry decoder portion GD comprises a decoding version of an advanced parallelogram prediction module APP', and performs prediction of the vertices according to their respective prediction mode information," (col 8, lines 43- 67; col 9, lines 1-15). The group (W, V, U, R) have been predicted/decoded. According to prior art reference, R is predicted by a specified prediction mode (col 1, lines 46-67; col 2, lines 1-3; Fig. 1). When there is only one cluster, or when “the dihedral angles of the 3D mesh model are evenly spread over a wide range,” only one prediction mode is selected for decoding and the vertices W, V, U will be predicted/decoded according to the same prediction mode as that used for R (col 6, lines 18-30; col 5, lines 22- 38). In the case of one cluster, the same prediction mode would be used for each group.)
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Chen to Kondrad. The motivation would have been “for increasing coding efficiency and improving prediction accuracy,” (Chen, col 3, lines 17-24).
Kondrad in view of Chen is not relied upon teaching but Sugio teaches and determining an upper limit of prediction candidates based on a syntax labeled "mesh position prediction max parallelograms minus1" (“N peripheral three-dimensional points of the three-dimensional point to be encoded that are used for prediction are N three-dimensional points encoded and decoded the distance from the three-dimensional point to be encoded is less than threshold THd. The maximum value of N may be added to the bitstream as NumNeighborPoint. The value of N need not always agree with the value of NumNeighborPoint, such as when the number of peripheral three-dimensional points encoded and decoded is less than the value of NumNeighborPoint,” para [0528]. The peripheral three-dimensional points read on prediction candidates. The maximum value reads on upper limit, para [0543]. NumNeighborPoint reads on “mesh_position_prediction_max_parallelograms_minus1” syntax. ).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Sugio to Kondrad in view of Chen. The motivation would have been to reduce the processing amount. By limiting the number of predictors / prediction candidates, the processing amount is reduced. Limited predictors/ prediction candidates enables fewer calculations, limits resource consumption, and enables faster, deterministic calculation times.
Regarding claim 2, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 1, wherein decoding the encoded volumetric data comprises applying parallelogram prediction in which the parallelogram is split into two triangles and first ones of first vertices of a first one of the two triangles is used as a predictor for second ones of second vertices of a second one of the two triangles (Kondrad; "Each new triangle is next to an already encoded one. This allows efficient compression of vertex coordinates and other attributes, such as normals. Instead of storing the absolute values, they may be predicted from an adjacent triangle (using a parallelogram prediction) and only store the difference between predicted and actual values, which is generally smaller as compared to the absolute values", para [189]. The triangles comprise vertices. The vertices of the already encoded triangle read on first ones of first vertices. The vertices of the new triangle read on second ones of second vertices.).
Regarding claim 3, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 2, wherein the first one of the two triangles comprises a vertex A, a vertex B, and a vertex C (Chen; reference triangle UVW comprising vertices U, V, and W respectively (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).), wherein the second one of the two triangles comprises the vertex B, the vertex C, and a vertex D (Chen; triangle URV comprising vertices U,V, and R respectively (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).), and wherein the parallelogram prediction comprises predicting a coordinate of vertex D based on coordinates of vertex A, vertex B, and vertex C (Chen; vertex A, vertex B, and vertex C are mapped to vertices U,V, and W respectively. Vertex D is mapped to vertex R (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Chen to Kondrad in view of Sugio. The motivation would have been to achieve high compression efficiency.
Regarding claim 5, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 2, wherein at least one of the vertices (Chen; vertex R (col 1, lines 46-67; col 2, lines 1-3; Fig. 1)) comprises one prediction candidate (Chen; The vertices U, V, W that comprise reference triangle UVW include and read on one prediction candidate (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Chen to Kondrad. The motivation would have been for “improving geometry compression efficiency,” (Chen; col 1, lines 46-67; col 2, lines 1-3).
Regarding claim 28, Kondrad teaches a non-transitory computer-readable storage medium storing instructions and a video bitstream that are generated by a video encoding method, the instructions, when executed by a computer, cause the computer to implement a video encoding method (“An example computer readable medium includes program instructions for causing an apparatus to perform at least the following: generate an extension to a volumetric video coding structure, wherein the extension to the volumetric coding structure enables at least one of the following: storage of information corresponding to an algorithm for compression of a mesh; prediction of single vertex values between mesh frames; generation of a volumetric video coding bitstream consisting of attribute video components that is mapped to the mesh; or conversion of a first file format to a second file format; and store a vertex of the mesh by using the extension,” (page 20, para [0159]).
"The example computer readable medium may further include, wherein the computer readable medium comprises a non-transitory computer readable medium," (page 21, para [0161]; page 10, para [0081]).) comprising:
obtaining a mesh representing volumetric data of at least one three-dimensional (3D) visual content ((page 20, para [0159]). The mesh to be compressed corresponds to a volumetric video. Volumetric video reads on three-dimensional (3D) visual content because a volumetric video captures a three-dimensional space. A volumetric video comprises volumetric data.);
and transmitting the video bitstream (“The communication interface 206 may be any means such as a device or circuitry embodied in either hardware or a combination of hardware and software that is configured to receive and/or transmit data, including video bitstreams,” (pages 36-37, para [0235]).
“…provide output to a user, such as by outputting an encoded video bitstream,” (page 37, para [0236]). (page 18, para [0139]).).
Kondrad is not relied upon teaching but Chen teaches partitioning a plurality of vertices of the mesh into a plurality of groups, at least one of the groups representing a shape of a parallelogram ("In one embodiment of the encoding method, in the first mode the enhanced prediction triangle corresponds to a co-planar parallelogram extension of the reference triangle that is rotated by said representative dihedral angle on the first axis, and wherein the enhanced prediction triangles of the first and second mode are co-planar and both have said side along the first axis common with the reference triangle," (col 3, lines 52- 67).
The enhanced prediction triangle that corresponds to a co-planar parallelogram extension of the reference triangle reads on representing the shape of a parallelogram. The enhanced prediction triangle that corresponds to a co-planar parallelogram extension of the reference triangle comprise more than one group, and thus reads on a plurality of groups. The triangles are partitioned vertices since the triangles comprise vertices (Abstract).); and
encoding the volumetric data by predicting the vertices in each group of the plurality of groups based on a prediction mode associated with said each group ("An encoder will choose the proper prediction mode for each vertex. The predicted position is generated by a rotation operation and, in one embodiment, by an additional mirror mapping operation after traditional parallelogram prediction. The rotation angle and whether to do the mirror mapping are decided according to the prediction mode," (col 5, lines 21-38).
The volumetric data comprises vertices. The verities are predicted based on a prediction mode.
“The prediction step exploits the correlation between adjacent vertex positions, which is most crucial in improving geometry compression efficiency. The most widely used prediction strategy is parallelogram prediction… This approach is shown in FIG. 1. The shaded area has already been encoded/decoded…,” (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).
From Chen’s teachings, it is clear that the prediction step can be applied in either the encoding or decoding phase. The group (W, V, U, R) have been predicted/ encoded. According to Chen, R is predicted by a specified prediction mode (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).
When there is only one cluster, or when “the dihedral angles of the 3D mesh model are evenly spread over a wide range,” only one prediction mode is selected for encoding and the vertices W, V, U will be predicted/encoded according to the same prediction mode as that used for R (col 6, lines 18-30; col 5, lines 22- 38). In the case of one cluster, the same prediction mode would be used for each group.)
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Chen to Kondrad. The motivation would have been “for increasing coding efficiency and improving prediction accuracy,” (Chen, col 3, lines 17-24).
Korndrad in view of Chen is not relied upon teaching but Sugio teaches and determining an upper limit of prediction candidates based on a syntax labeled “mesh_position_prediction_max_parallelograms_minus1” (“N peripheral three-dimensional points of the three-dimensional point to be encoded that are used for prediction are N three-dimensional points encoded and decoded the distance from the three-dimensional point to be encoded is less than threshold THd. The maximum value of N may be added to the bitstream as NumNeighborPoint. The value of N need not always agree with the value of NumNeighborPoint, such as when the number of peripheral three-dimensional points encoded and decoded is less than the value of NumNeighborPoint,” para [0528]. The peripheral three-dimensional points read on prediction candidates. The maximum value reads on upper limit, para [0543]. NumNeighborPoint reads on “mesh_position_prediction_max_parallelograms_minus1” syntax.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Sugio to Kondrad in view of Chen. The motivation would have been to reduce the processing amount. By limiting the number of predictors / prediction candidates, the processing amount is reduced. Limited predictors/ prediction candidates enables fewer calculations, limits resource consumption, and enables faster, deterministic calculation times.
Regarding claim 21, it is rejected using the same citations and rationales described in the rejection of claim 28. Claim 21 additionally recites the method performed by at least one processor. Kondrad teaches the method performed by at least one processor (Kondrad; “An example apparatus includes at least one processor; and at least one non-transitory memory comprising computer program code; wherein the at least one memory and the computer program code are configured to, with the at least one processor, cause the apparatus at least to perform: generate an extension to a volumetric video coding structure, wherein the extension to the volumetric coding structure enables at least one of the following: storage of information corresponding to an algorithm for compression of a mesh; prediction of single vertex values between mesh frames; generation of a volumetric video coding bitstream consisting of attribute video components that is mapped to the mesh; or conversion of a first file format to a second file format; and storing a vertex of the mesh by using the extension,” (page 10, para [0081]).).
Regarding claim 25, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 22, wherein at least one of the vertices (Chen; vertex R (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).) comprises one prediction candidate (Chen; The vertices U, V, W that comprise reference triangle UVW include and read on one prediction candidate (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Chen to Kondrad. The motivation would have been for “improving geometry compression efficiency,” (Chen; col 1, lines 46-67; col 2, lines 1-30).
Regarding claim 29, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 28, wherein encoding the volumetric data comprises applying parallelogram prediction in which the parallelogram is split into two triangles and first ones of first vertices of a first one of the two triangles is used as a predictor for second ones of second vertices of a second one of the two triangles (Kondrad; "Each new triangle is next to an already encoded one. This allows efficient compression of vertex coordinates and other attributes, such as normals. Instead of storing the absolute values, they may be predicted from an adjacent triangle (using a parallelogram prediction) and only store the difference between predicted and actual values, which is generally smaller as compared to the absolute values", (pages 25-26, para [0185]-[0189]).).
Regarding claim 22, it is rejected using the same citations and rationales described in the rejection of claim 29.
Regarding claim 30, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 29, wherein the first one of the two triangles comprises a vertex A, a vertex B, and a vertex C (Chen; reference triangle UVW comprising vertices U, V, and W respectively (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).), wherein the second one of the two triangles comprises the vertex B, the vertex C, and a vertex D (Chen; triangle URV comprising vertices U,V, and R respectively (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).), and wherein the parallelogram prediction comprises predicting a coordinate of vertex D based on coordinates of vertex A, vertex B, and vertex C (Chen; vertex A, vertex B, and vertex C are mapped to vertices U,V, and W respectively. Vertex D is mapped to vertex R (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Chen to Kondrad in view of Sugio. The motivation would have been to achieve high compression efficiency.
Regarding claim 23, it is rejected using the same citations and rationales described in the rejection of claim 30.
Regarding claim 31, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 29, wherein at least one of the vertices (Chen; vertex R (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).) comprises any of no prediction candidates and one prediction candidate (Chen; The vertices U, V, W that comprise reference triangle UVW include and read on one prediction candidate (col 1, lines 46-67; col 2, lines 1-3; Fig. 1).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Chen to Kondrad. The motivation would have been for “improving geometry compression efficiency,” (Chen; col 1, lines 46-67; col 2, lines 1-3).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Kondrad in view of Chen in further view of Sugio in further view of Guillaume (GB 2561824 A).
Regarding claim 4, Kondrad in view of Chen in further view of Sugio is not relied upon teaching but Guillaume teaches the method according to claim 2, wherein at least one of the vertices comprises no prediction candidates (The starting vertex reads on at least one of the vertices. Since the starting vertex is not predicted, it comprises no prediction candidates, (page 12, lines 37-38; page 13, lines 1-2).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Guillaume to Kondrad in view of Chen. The motivation would have been to allow the compression algorithm to function even when there is no immediately available reference point to predict from.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Kondrad in view of Chen in further view of Sugio in further view of Vytyaz (US 20220020211 A1).
Regarding claim 6, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 2, wherein at least one of the vertices comprises more than one prediction candidate (Chen; Fig. 4 showing multi-way parallelogram prediction (col 5, line 2). “Another approach1 uses a multi-way parallelogram prediction scheme shown in FIG. 4. The multi-way prediction exploits all possible reference triangles and uses the average of all single-way predicted positions as the multi-way prediction result… 1D. Cohen-Or, R. Cohen, and R. Irony: "Multiway geometry encoding", Technical report, School of Computer Science, Tel Aviv University, 2002.” (Chen; col 2, lines 18-30). The reference triangles include and read on more than one prediction candidate.), and
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Chen to Kondrad in view of Sugio. The motivation would have been to improve compression efficiency.
Kondrad in view of Chen in further view of Sugio is not relied upon teaching but Vytyaz teaches the parallelogram prediction comprises determining an average of candidates of the more than one prediction candidate (“For instance, a multi-per-corner prediction (e.g., multi-parallelogram prediction) obtains a predicted value associated with every available corner; a combined predicted primary attribute value for the vertex is then computed as an average of the predicted values associated with all available corners. A residual is then computed with respect to the final predicted value,” (pages 6-7, para [0069]).
The disclosed corner reads on prediction candidate because it is associated with a particular face of the mesh, (page 4, para [0035]). Additionally, the corner is used in multi-parallelogram prediction which “uses information from all opposite faces opposite a vertex,” (page 3, para [0026]). The disclosed average of the predicted values reads on average of candidates. Additionally, “the predicted primary attribute value can include a predicted position of the vertex,” (page 2, para [0010]).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Vytyaz to Kondrad in view of Chen. The motivation would have been to result in “better prediction than traditional parallelogram prediction,” (Vytyaz; page 3, para [0026]).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Kondrad in view of Chen in further view of Sugio in further view of Lee et al. (WO 2022015006 A1; hereinafter Lee).
Regarding claim 9, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 1, wherein an upper limit of prediction candidates is signaled in the bitstream by a syntax labeled “mesh_position_prediction_max_parallelograms_minus1” (Sugio; “N peripheral three-dimensional points of the three-dimensional point to be encoded that are used for prediction are N three-dimensional points encoded and decoded the distance from the three-dimensional point to be encoded is less than threshold THd. The maximum value of N may be added to the bitstream as NumNeighborPoint. The value of N need not always agree with the value of NumNeighborPoint, such as when the number of peripheral three-dimensional points encoded and decoded is less than the value of NumNeighborPoint,” (Sugio; para [0528], para [0543]). The peripheral three-dimensional points read on prediction candidates. The maximum value reads on upper limit (Sugio; para [0543]). NumNeighborPoint reads on mesh_position_prediction_max_parallelograms_minus1 syntax.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Sugio to Kondrad in view of Chen. The motivation would have been to reduce the processing amount. By limiting the number of predictors / prediction candidates, the processing amount is reduced. Limited predictors/ prediction candidates enables fewer calculations, limits resource consumption, and enables faster, deterministic calculation times.
Kondrad in view of Chen in further view of Sugio is not relied upon teaching but Lee teaches a lifting_max_num_direct_predictors field that indicates a maximum number of predictors and indicates a range of 0 to 7, inclusive, as the upper limit (Lee; “The lifting_max_num_direct_predictors field indicates the maximum number of predictors to be used for direct prediction. The value of the lifting_max_num_direct_predictors field is in the range of 0 to LevelDetailCount,” (page 53; Fig 9; Fig 8).
“The variable LevelDetailCount for specifying the number of LODs can be obtained by adding 1 to the value of the lifting_num_detail_levels_minus1 field (LevelDetailCount =lifting_num_detail_levels_minus1 + 1),” (page 52).
The maximum number of predictors reads on upper limit. Lee teaches a range of 0 to LevelDetailCount, wherein the LevelDetailCount is a predetermined positive integer. Fig. 9 shows LevelDetailCount could be 2, and the range includes LOD0, LOD1, LOD2. Fig. 8 shows an example of total 7 levels of details, and the LevelDetailCount could be 6 or 7. Although Lee does not explicitly teach the range 0 to 7, the range 0 to 7 would have been obvious in view of Lee’s range of 0 to LevelDetailCount in view of MPEP 2144.05 “Obviousness of Similar and Overlapping Ranges…”).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Lee to Kondrad in view of Chen in further view of Sugio. The motivation would have been to improve efficiency and reduce the processing amount by limiting the number of predictors / prediction candidates. Additional motivation would have been to bound computational complexity and limit worst-case processing latencies.
Claim 24 is rejected under 35 U.S.C. 103 as being unpatentable over Kondrad in view of Chen in further view of Sugio in further view of Guillaume (GB 2561824 A).
Regarding claim 24, Kondrad in view of Chen in further view of Sugio is not relied upon teaching but Guillaume teaches the method according to claim 22, wherein at least one of the vertices comprises any of no prediction candidates (The first/starting vertex reads on at least one of the vertices. Since the first/starting vertex is not predicted, it comprises no prediction candidates, (page 12, lines 32-38; page 13, lines 1-2).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Guillaume to Kondrad in view of Chen. The motivation would have been to allow the compression algorithm to function even when there is no immediately available reference point to predict from.).
Claims 26 and 32 are rejected under 35 U.S.C. 103 as being unpatentable over Kondrad in view of Chen in further view of Sugio in further view of Vytyaz (US 20220020211 A1).
Regarding claim 32, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 29, wherein at least one of the vertices comprises more than one prediction candidate (Chen; Fig. 4 showing multi-way parallelogram prediction (col 5, line 2). “Another approach1 uses a multi-way parallelogram prediction scheme shown in FIG. 4. The multi-way prediction exploits all possible reference triangles and uses the average of all single-way predicted positions as the multi-way prediction result… 1D. Cohen-Or, R. Cohen, and R. Irony: "Multiway geometry encoding", Technical report, School of Computer Science, Tel Aviv University, 2002.” (Chen; col 2, lines 18-30). The reference triangles include and read on more than one prediction candidate.), and
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Chen to Kondrad in view of Sugio. The motivation would have been to improve compression efficiency.
Kondrad in view of Chen in further view of Sugio is not relied upon teaching but Vytyaz teaches the parallelogram prediction comprises determining an average of candidates of the more than one prediction candidate (“For instance, a multi-per-corner prediction (e.g., multi-parallelogram prediction) obtains a predicted value associated with every available corner; a combined predicted primary attribute value for the vertex is then computed as an average of the predicted values associated with all available corners. A residual is then computed with respect to the final predicted value,” (pages 6-7, para [0069]).
The disclosed corner reads on prediction candidate because it is associated with a particular face of the mesh, (page 4, para [0035]). Additionally, the corner is used in multi-parallelogram prediction which “uses information from all opposite faces opposite a vertex,” (page 3, para [0026]). The disclosed average of the predicted values reads on average of candidates. Additionally, “the predicted primary attribute value can include a predicted position of the vertex,” (page 2, para [0010]).).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Vytyaz to Kondrad in view of Chen. The motivation would have been to result in “better prediction than traditional parallelogram prediction,” (Vytyaz; page 3, para [0026]).
Regarding claim 26, it is rejected using the same citations and rationales described in the rejection of claim 32.
Claims 27 and 33 are rejected under 35 U.S.C. 103 as being unpatentable over Kondrad in view of Chen in further view of Sugio in further view of Lee et al. (WO 2022015006 A1; hereinafter Lee).
Regarding claim 33, Kondrad in view of Chen in further view of Sugio teaches the method according to claim 28, wherein an upper limit of prediction candidates is signaled in the video bitstream by a syntax labeled " mesh_position_prediction_max_parallelograms_minus1” Sugio; “N peripheral three-dimensional points of the three-dimensional point to be encoded that are used for prediction are N three-dimensional points encoded and decoded the distance from the three-dimensional point to be encoded is less than threshold THd. The maximum value of N may be added to the bitstream as NumNeighborPoint. The value of N need not always agree with the value of NumNeighborPoint, such as when the number of peripheral three-dimensional points encoded and decoded is less than the value of NumNeighborPoint,” (Sugio; para [0528], para [0543]). The peripheral three-dimensional points read on prediction candidates. The maximum value reads on upper limit (Sugio; para [0543]). NumNeighborPoint reads on mesh_position_prediction_max_parallelograms_minus1 syntax.).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Sugio to Kondrad in view of Chen. The motivation would have been to reduce the processing amount. By limiting the number of predictors / prediction candidates, the processing amount is reduced. Limited predictors/ prediction candidates enables fewer calculations, limits resource consumption, and enables faster, deterministic calculation times.
Kondrad in view of Chen in further view of Sugio is not relied upon teaching but Lee teaches a lifting_max_num_direct_predictors field that indicates a maximum number of predictors and indicates a range of 0 to 7, inclusive, as the upper limit (Lee; “The lifting_max_num_direct_predictors field indicates the maximum number of predictors to be used for direct prediction. The value of the lifting_max_num_direct_predictors field is in the range of 0 to LevelDetailCount,” (page 53; Fig 9; Fig 8).
“The variable LevelDetailCount for specifying the number of LODs can be obtained by adding 1 to the value of the lifting_num_detail_levels_minus1 field (LevelDetailCount =lifting_num_detail_levels_minus1 + 1),” (page 52).
The maximum number of predictors reads on upper limit. Lee teaches a range of 0 to LevelDetailCount, wherein the LevelDetailCount is a predetermined positive integer. Fig. 9 shows LevelDetailCount could be 2, and the range includes LOD0, LOD1, LOD2. Fig. 8 shows an example of total 7 levels of details, and the LevelDetailCount could be 6 or 7. Although Lee does not explicitly teach the range 0 to 7, the range 0 to 7 would have been obvious in view of Lee’s range of 0 to LevelDetailCount in view of MPEP 2144.05 “Obviousness of Similar and Overlapping Ranges…”).
Before the effective filling date of the claimed invention, it would have been obvious to one having ordinary skill in the art to apply the teachings of Lee to Kondrad in view of Chen in further view of Sugio. The motivation would have been to improve efficiency and reduce the processing amount by limiting the number of predictors / prediction candidates. Additional motivation would have been to bound computational complexity and limit worst-case processing latencies.
Regarding claim 27, it is rejected using the same citations and rationales described in the rejection of claim 33.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ERICA G THERKORN whose telephone number is (571)272-2939. The examiner can normally be reached Monday - Friday 9:00am - 5:00pm.
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, Devona Faulk can be reached at 571-272-7515. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ERICA G THERKORN/ Examiner, Art Unit 2618
/DEVONA E FAULK/ Supervisory Patent Examiner, Art Unit 2618
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