Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 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.
Claim(s) 1-2, 4, 11, 15-17, 19, 26, and 30 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hemmer et al. (U.S. PGPUB 20200265552) in view of Munkberg et al. (U.S. PGPUB 20220165040) and further in view of Deering (U.S. Patent No. 6,313,838).
With respect to claim 1, Hemmer et al. disclose a computer-implemented method of generating a level of detail (LOD) to be used to render a computer-generated three-dimensional model, the method comprising:
generating a minimum LOD for a three-dimensional model (paragraph 60, the LOD reduction manager 140 also produces a very low LOD known as an abstraction LOD); and
generating an experimental rendering of the three-dimensional model in a predefined scene using the minimum LOD (paragraph 73, The abstraction process 400 involves using mesh decimation operations, starting with the reference mesh 402(A) and ending with the abstraction mesh 404(A). In some implementations, the abstraction mesh 404(A) is defined to be that mesh resulting from repeated mesh decimation operations that is as coarse as possible while having a distortion value not exceeding a user-specified maximum distortion, paragraph 110, The progressive bitstream 380 includes a header 382 generated from the single-rate geometry encoding operation 370 on the lowest LOD 362. The header 382 records the encoded mesh of the lowest LOD 362, the lowest resolution texture encoded via progressive JPEG, the number of bits used for XYZ and UV coordinates, and the bounding box required to reverse the quantization operations). However, Hemmer et al. do not expressly disclose generating a reference rendering of the three-dimensional model in the predefined scene using an original model for the three-dimensional model; calculating an image quality metric for the experimental rendering indicating a visual degradation of the experimental rendering compared to the reference rendering; determining whether the minimum LOD satisfies an image quality target based on the image quality metric for the experimental rendering; and responsive to a determination that the minimum LOD does not satisfy the image quality target, selecting an LOD that satisfies the image quality target from a set of one or more candidate LODs based on a second metric.
Munkberg et al., who also deal with LOD rendering, disclose a method for generating a reference rendering of the three-dimensional model in the predefined scene using an original model for the three-dimensional model (paragraph 27, Reference images 124 are generated by rendering a reference 3D model according to the environmental conditions 108);
calculating an image quality metric for the experimental rendering indicating a visual degradation of the experimental rendering compared to the reference rendering (paragraph 29, An image space loss unit 120 processes the reference images 124 and the images 112 to produce the image space losses 122. Corresponding images from the images 112 and reference images 124 for each particular environmental configuration 108 are compared to compute the image space losses 122); and
determining whether the minimum LOD satisfies an image quality target based on the image quality metric for the experimental rendering (paragraph 29, The initial 3D model 105 is adjusted based on the image space losses 122 to produce the reduced resolution 3D model 110. The reduced resolution 3D model 110 may be further refined until the image space losses 122 are reduced to a target value). The image space loss unit calculates an image quality metric indicating a visual degradation (paragraph 21, The parameters are updated based on image space losses (e.g., pixel differences) between rendered images of the initial 3D model and the reference 3D model).
Hemmer et al. and Munkberg et al. are in the same field of endeavor, namely computer graphics.
Before the effective filing date of the claimed invention, it would have been obvious to apply the method of generating a reference rendering of the three-dimensional model in the predefined scene using an original model for the three-dimensional model; calculating an image quality metric for the experimental rendering indicating a visual degradation of the experimental rendering compared to the reference rendering; and determining whether the minimum LOD satisfies an image quality target based on the image quality metric for the experimental rendering, as taught by Munkberg et al., to the Hemmer et al. system, because the search for the shape and appearance of the 3D model is driven by image space error and the shape and appearance are simultaneously optimized. Therefore, each stage of the forward rendering model (e.g., geometry, shading, normal maps, displacement maps, transparency, and the like) can specialize for the effects that the particular stage captures best, “negotiating” how to achieve the desired outcome together (paragraph 24 of Munkberg et al.).
Deering, who also deal with LOD rendering, disclose a method, responsive to a determination that the minimum LOD does not satisfy the image quality target, selecting an LOD that satisfies the image quality target from a set of one or more candidate LODs based on a second metric (column 21, lines 49-57, In some other applications, the control constant may be image quality, rather than frame rate. Because rendered image quality is related to keeping the size of the majority of polygons below the Nyquist rate of the combination of the display system, the physical viewer's perception ability, and the image content, the curves also provide a formal method of controlling image quality. Specifically, a user may wish to choose a level of detail object…, column 25, lines 62-67, column 26, lines 1-5, These object variants may themselves comprise a plurality of polygons and corresponding rendering attribute information (e.g., textures). The object variants may correspond to differing levels of detail (LOD), and may be selected before or during the rendering process to achieve a predetermined minimum frame rate (e.g., in step 332 of FIG. 19A)). The size of the majority of polygons corresponds to the second metric.
Hemmer et al., Munkberg et al., and Deering are in the same field of endeavor, namely computer graphics.
Before the effective filing date of the claimed invention, it would have been obvious to apply the method responsive to a determination that the minimum LOD does not satisfy the image quality target, selecting an LOD that satisfies the image quality target from a set of one or more candidate LODs based on a second metric, as taught by Deering, to the Hemmer et al. system, because this would implement a graphics system capable of efficiently determining the performance limits for a particular scene and efficiently determining graphics system performance limits (column 3, lines 47-50 of Deering).
With respect to claim 2, Hemmer et al. as modified by Munkberg et al. and Deering disclose the computer-implemented method of claim 1, wherein the minimum LOD is generated using an existing mesh decimation method (Hemmer et al.: paragraph 72, to generate the abstraction mesh 312, the LOD reduction manager 140 performs a sequence of mesh decimation operations on the reference mesh 306 until the measure of distortion between the abstraction mesh 312 and the reference mesh 306 is greater than a specified distortion value).
With respect to claim 4, Hemmer et al. as modified by Munkberg et al. and Deering disclose the computer-implemented method of claim 1, wherein reference rendering comprises a rendering of the three-dimensional model generated without applying an LOD to modify the original model for the three-dimensional model (Munkberg et al.: paragraph 27, Reference images 124 are generated by rendering a reference 3D model according to the environmental conditions 108. In an embodiment, the reference images 124 comprise a video or animation sequence of the reference 3D model in motion and/or deforming). References images 124 are rendered without applying an LOD, as they are generated according to environmental conditions.
With respect to claim 11, Hemmer et al. as modified by Munkberg et al. and Deering disclose the computer-implemented method of claim 1, wherein selecting the LOD that satisfies the image quality target from the set of one or more candidate LODs based on the second metric comprises: generating one or more candidate LODs using a two-dimensional function of mesh number of triangles and/or vertices and texture pixel dimensions and/or quality (Hemmer et al.: paragraph 68, At 208, the cost metric manager 160 generates a respective value of a LOD cost metric associated with each of the plurality of candidate LODs, Hemmer et al.: paragraph 82, Mesh decimation operation 324, Hemmer et al.: paragraph 85, Texture reduction operation 330); filtering out candidate LODs that do not satisfy the image quality target (Hemmer et al.: paragraph 90, As shown in FIG. 3, the mesh data of the reduced LOD 362, if the stop condition 366 is achieved, is single-rate encoded with lowered quantization bits to produce a single-rate geometry encoding 370); and selecting the remaining candidate LOD with an optimal value for the second metric (Deering: column 21, lines 55-57, a user may wish to choose a level of detail object such that for the current s, f(l) is 0.5 or less (e.g., to keep the median area sub-pixel)).
With respect to claim 15, Hemmer et al. as modified by Munkberg et al. and Deering disclose the computer-implemented method of claim 1, wherein the image quality metric calculated for the experimental rendering is a structural similarity index measure (SSIM) as compared to the reference rendering, and wherein the image quality target comprises a maximum acceptable deviation from the reference rendering (Hemmer et al.: paragraph 73, the mesh decimation uses a quadric error metric until the multi-scale structural similarity (MS-SSIM) distortion of a textured abstraction exceeds a user-defined tolerance). However, Hemmer et al. do not expressly disclose the image quality target comprising a value between 0.80 and 0.85.
At the time of the invention was made, it would have been an obvious matter of design choice to a person of ordinary skill in the art to modify Hemmer et al. to include the image quality target comprising a value between 0.80 and 0.85 because Applicant has not disclosed that using a using an SSIM between 0.80 and 0.85 provides an advantage, is used for a particular purpose, or solves a stated problem (page 11, paragraph 24 of Specification, For example, if SSIM is used, a value between 0.80 and 0.85 may be used as the image quality target). Therefore, it would have been an obvious matter of design choice to modify Hemmer et al. to obtain the invention as specified in claim 15.
With respect to claim 16, Hemmer et al. as modified by Munkberg et al. and Deering disclose a system for generating a level of detail (LOD) to be used to render a computer-generated three-dimensional model (Hemmer et al.: paragraph 129, FIG. 12 illustrates an example of a generic computer device 1200), the system comprising: one or more processors configured by computer readable instructions (Hemmer et al.: paragraph 131, Computing device 1200 includes a processor 1202, memory 1204, a storage device 1206, a high-speed interface 1208 connecting to memory 1204 and high-speed expansion ports 1210) to execute the method of claim 1; see rationale for rejection of claim 1.
With respect to claim 17, Hemmer et al. as modified by Munkberg et al. and Deering disclose the system of claim 16 for executing the method of claim 2; see rationale for rejection of claim 2.
With respect to claim 19, Hemmer et al. as modified by Munkberg et al. and Deering disclose the system of claim 18 for executing the method of claim 4; see rationale for rejection of claim 4.
With respect to claim 26, Hemmer et al. as modified by Munkberg et al. and Deering disclose the system of claim 16 for executing the method of claim 11; see rationale for rejection of claim 11.
With respect to claim 30, Hemmer et al. as modified by Munkberg et al. and Deering disclose the system of claim 18 for executing the method of claim 15; see rationale for rejection of claim 15.
Claim(s) 5-6 and 20-21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hemmer et al. (U.S. PGPUB 20200265552) in view of Munkberg et al. (U.S. PGPUB 20220165040), Deering (U.S. Patent No. 6,313,838), and further in view of Isaacs (U.S. Patent No. 5,894,308).
With respect to claim 5, Hemmer et al. as modified by Munkberg et al. and Deering disclose the computer-implemented method of claim 1. However, Hemmer et al. as modified by Munkberg et al. and Deering do not expressly disclose calculating an image quality metric for the reference rendering; and determining whether the minimum LOD satisfies the image quality target based on the image quality metric for the experimental rendering and the image quality metric for the reference rendering.
Isaacs, who also deals with LOD rendering, discloses a method for calculating an image quality metric for the reference rendering; and determining whether the minimum LOD satisfies the image quality target based on the image quality metric for the experimental rendering and the image quality metric for the reference rendering (column 14, lines 10-19, Once the number of triangles has been reduced to a suitably low number while maintaining an acceptably high level of image quality, the user may click on the Accept button 407 to create a computer file of the 3D object at the current LOD. After creating the desired number of LOD files, the user may use another tool (e.g., Silicon Graphics' Level of Detail Editor) to associate each LOD file with a particular viewing range).
Hemmer et al., Munkberg et al., Deering, and Isaacs are in the same field of endeavor, namely computer graphics.
Before the effective filing date of the claimed invention, it would have been obvious to apply the method of calculating an image quality metric for the reference rendering; and determining whether the minimum LOD satisfies the image quality target based on the image quality metric for the experimental rendering and the image quality metric for the reference rendering, as taught by Isaacs, to the Hemmer et al. as modified by Munkberg et al. and Deering system, because this provides an ideal environment for 3D authors to create multiple LODs for each object and interactively fine-tune each level for optimal balance of performance and image quality (column 4, lines 34-37 of Isaacs).
With respect to claim 6, Hemmer et al. as modified by Munkberg et al., Deering, and Isaacs disclose the computer-implemented method of claim 5, wherein the image quality target comprises a maximum acceptable deviation from a rendering, wherein determining whether the minimum LOD satisfies the image quality target comprises: determining whether the image quality metric for the experimental rendering is within the maximum acceptable deviation of the image quality metric for the reference rendering (Isaacs: column 9, lines 21-29, As the user moves slider 423 even closer to the maximum value (e.g., to 0.30 as illustrated in FIGS. 11a and 11b), the Current Triangle Count is reduced to such a low level (78 triangles or 8% of Original Triangle Count) that the 3D object image becomes less cohesive and thus less recognizable, with gaps 501 forming in the object. Depending on the application and the associated viewing range, the object illustrated in FIGS. 11a and 11b might represent an unacceptably low quality image for any LOD).
With respect to claim 20, Hemmer et al. as modified by Munkberg et al., Deering, and Isaacs disclose the system of claim 18 for executing the method of claim 5; see rationale for rejection of claim 5.
With respect to claim 21, Hemmer et al. as modified by Munkberg et al., Deering, and Isaacs disclose the system of claim 20 for executing the method of claim 6; see rationale for rejection of claim 6.
Claim(s) 7-10, 12-14, 22-25, and 27-29 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hemmer et al. (U.S. PGPUB 20200265552) in view of Munkberg et al. (U.S. PGPUB 20220165040), Deering (U.S. Patent No. 6,313,838) and further in view of Raymond (U.S. PGPUB 20220096931).
With respect to claim 7, Hemmer et al. as modified by Munkberg et al. and Deering disclose the computer-implemented method of claim 1. However, Hemmer et al. as modified by Munkberg et al. and Deering do not expressly disclose the method further comprising receiving one or more input parameters, wherein the one or more input parameters include at least the image quality metric.
Raymond, who also deals with LOD rendering, discloses a method further comprising receiving one or more input parameters, wherein the one or more input parameters include at least the image quality metric (paragraph 211, At step 606, based on monitoring of one or more of the first plurality of variables, the rendering module 134 determines if one or more of a plurality of corrective factors should be applied to the offline authored switch distances associated with each LOD of the chain of LOD assets).
Hemmer et al., Munkberg et al., Deering, and Raymond are in the same field of endeavor, namely computer graphics.
Before the effective filing date of the claimed invention, it would have been obvious to apply the method further comprising receiving one or more input parameters, wherein the one or more input parameters include at least the image quality metric, as taught by Raymond, to the Hemmer et al. as modified by Munkberg et al. and Deering system, because this would determine optimal selection of LOD assets, during runtime, by integrating a plurality of variables into a LOD selection and rendering process (paragraph 11 of Raymond).
With respect to claim 8, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the computer-implemented method of claim 7, wherein the at least one input parameter specifies the predefined scene (Raymond: paragraph 175, At runtime, the rendering module or engine 134 (in data communication with a client-side rendering module or engine 134′) implements a plurality of instructions or programmatic code to determine which representation, version or LOD, out of a set, group or chain of LOD assets, to render for a given gameplay view or scene).
With respect to claim 9, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the computer-implemented method of claim 7, wherein the at least one input parameters specifies a range of distances, wherein the experimental rendering and the reference rendering are generated by rendering the three-dimensional model in the predefined scene at one or more distances within the range of distances (Raymond: paragraph 210, At step 604, the rendering module 134 monitors one or more of a first plurality of variables related to a player's gameplay and/or client device 110, Raymond: paragraph 213, At step 614, the module 134 proceeds to render the selected LOD from the chain of LOD assets).
With respect to claim 10, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the computer-implemented method of claim 7, the method further comprising assigning the selected LOD as an LOD to be used to render the three-dimensional model according to the one or more input parameters (Raymond: paragraph 212, However, if it is determined that none of the plurality of corrective factors need to be applied, then, at step 612, the rendering module 134 selects a LOD, from the chain of LOD assets, on the basis of its corresponding offline authored switch distance).
With respect to claim 12, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the computer-implemented method of claim 11, wherein selecting the remaining candidate LOD with the optimal value for the second metric comprises selecting the remaining candidate LOD with the highest value of the remaining candidate LOD with the lowest value based on the second metric (Raymond: paragraph 207, the LOD fallback plan is directed towards rendering a less complex LOD, from a chain of LOD assets, if a more complex LOD cannot be rendered on-demand due to streaming bandwidth degradation and/or memory usage spikes. Stated differently, if LOD0 cannot be rendered then the module 134 would automatically attempt to render LOD1 and if LOD1 also cannot be rendered (that is, the streaming bandwidth and/or memory availability is not sufficient to enable rendering LOD1) then the module 134 would automatically fallback to rendering LOD2 and so on). Raymond selects the highest LOD based on available memory. It would have been obvious to apply the teachings of Raymond because this determine optimal selection of LOD assets, during runtime, by integrating a plurality of variables into a LOD selection and rendering process (paragraph 11 of Raymond).
With respect to claim 13, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the computer-implemented method of claim 1, wherein the second metric comprises a byte size of compressed meshes and/or textures for the three-dimensional model (Raymond: paragraph 175, the module 134 needs to select an appropriate LOD at an appropriate switch distance so as to enable consistent visuals and performance for all gameplay scenes across platforms while ensuring optimal runtime efficiency in terms of, at least, predefined target GPU performance and memory usage, Raymond: paragraph 194, To avoid visual artifacts (such as flickering) while skinning all visible LODs, the module 134 is configured to monitor and determine if a first predetermined memory space threshold, for the UAV, is being exceeded while rendering a gameplay scene). The LODs comprising the meshes and/or textures occupy memory space, which is measured in bytes.
With respect to claim 14, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the computer-implemented method of claim 1, wherein the second metric comprises an amount of Video RAM (VRAM) storage needed to store meshes and/or textures for the three-dimensional model (Raymond: paragraph 175, the module 134 needs to select an appropriate LOD at an appropriate switch distance so as to enable consistent visuals and performance for all gameplay scenes across platforms while ensuring optimal runtime efficiency in terms of, at least, predefined target GPU performance and memory usage, Raymond: paragraph 194, To avoid visual artifacts (such as flickering) while skinning all visible LODs, the module 134 is configured to monitor and determine if a first predetermined memory space threshold, for the UAV, is being exceeded while rendering a gameplay scene). The memory of the GPU is defined by VRAM.
With respect to claim 22, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the system of claim 16 for executing the method of claim 7; see rationale for rejection of claim 7.
With respect to claim 23, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the system of claim 22 for executing the method of claim 8; see rationale for rejection of claim 8.
With respect to claim 24, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the system of claim 22 for executing the method of claim 9; see rationale for rejection of claim 9.
With respect to claim 25, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the system of claim 22 for executing the method of claim 10; see rationale for rejection of claim 10.
With respect to claim 27, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the system of claim 26 for executing the method of claim 12; see rationale for rejection of claim 12.
With respect to claim 28, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the system of claim 16 for executing the method of claim 13; see rationale for rejection of claim 13.
With respect to claim 29, Hemmer et al. as modified by Munkberg et al., Deering, and Raymond disclose the system of claim 16 for executing the method of claim 14; see rationale for rejection of claim 14.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1 and 16 have been considered but are moot in view of the new ground(s) of rejection.
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 ANDREW GUS YANG whose telephone number is (571)272-5514. The examiner can normally be reached M-F 9 AM - 5:30 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kent Chang can be reached at (571)272-7667. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANDREW G YANG/Primary Examiner, Art Unit 2614
6/24/26
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