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 .
This action is in response to the Amendment filed on 6/29/2026.
Claims 2-12, 14-20are pending. Claims 2, 9, 12, 18, 19 been amended. Claims 1, 13 have been cancelled.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 6/29/2026 has been entered.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 2, 3, 4, 12, and 17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 17, and 21 of U.S. Patent No. 11,893,673 B2 (from application 17/287,254). Although the claims at issue are not identical, they are not patentably distinct from each other because they claim substantially the same subject matter and limitations as explained below.
Claim 2 is rejected as being obvious in light of claim 1 of U.S. Patent No. 11,893,673 B2.
Instant application claim 2
U.S. Patent No. 11,893,673 B2 – claim 1
2. A method for generating a weighted interpolation between two or more Morph Target Shapes relative to a Base Shape, the Morph Target Shapes each including a plurality of topologically consistent vertex coordinates, including the steps of: receiving a plurality of Input Constraint Shapes including a plurality of vertex coordinates topologically consistent with those of the Morph Target Shapes, each Input Constraint Shape associated with non-zero weights on one or more of the Morph Target Shapes; generating Additional Constraint Shapes for a plurality of new weightings on Morph Target Shapes using the Input Constraint Shapes, and associating the Additional Constraint Shapes with their respective new weightings; receiving interpolation weightings for each of the two or more Morph Target Shapes; generating an Interpolation Function for interpolating between the two or more Morph Target Shapes using the Base Shape, Input Constraint Shapes and Additional Constraint Shapes, wherein the Interpolation Function comprises a first term incorporating a weighted combination of Morph Target Shapes and a second term incorporating a weighted combination of Constraint Shapes; generating, using the Interpolation Function and using interpolation weightings as arguments to the Interpolation Function, vertex coordinates corresponding to the weighted interpolation between the two or more Morph Target Shapes.
1. A method for generating a weighted interpolation between a plurality n of morph target shapes B1 . . . Bn relative to a base shape B0 including the steps of: receiving a set of weights W, including for each morph target shape Bk of the morph target shapes B1 . . . Bn, a weight wk to be applied to that morph target shape Bk; receiving a plurality m of constraint shapes C1 . . . Cm, each constraint shape associated with non-zero weights (associated weights) on one or more of the morph target shapes B1 . . . Bn (associated shapes); generating a continuous multivariate interpolation function configured to reproduce each morph target shape and each constraint shape when a respective morph target shape or a constraint shape's associated weights on associated shapes are provided as arguments to the interpolation function; and using the weights W to be applied to morph target shapes as arguments of the interpolation function to generate the weighted interpolation, wherein the interpolation function has the form: f(W) = B0 + Σk=1..n (wk·ΔBk) + Σi=1..m (βi·ΔCi) wherein ΔBk represents a modified morph target shape; ΔCi represents a modified constraint shape; and βi represents a modifier applied to each constraint shape Ci; wherein the interpolation function is configured to make the interpolation function hold for all constraint shapes C1 . . . Cm.
Parent claim 1 recites each core limitation of instant claim 2: a weighted interpolation between morph target shapes and a base shape, constraint shapes associated with non-zero weights on the morph target shapes, and using weights as arguments of a multivariate interpolation function to generate the weighted interpolation. The newly added "first term/second term" limitation is expressly disclosed by the parent's interpolation function form f(W) = B0 + Σk=1..n (wk·ΔBk) + Σi=1..m (βi·ΔCi), where the first summation is a weighted combination of Morph Target Shapes and the second summation is a weighted combination of Constraint Shapes. The recited generation of "Additional Constraint Shapes" at new weightings is encompassed by the parent's requirement that the interpolation function hold for all constraint shapes, and "topologically consistent vertex coordinates" is inherent to a single multivariate function that reproduces each shape from weighted vertex combinations.
Claim 3 is rejected as being obvious in light of claim 17 of U.S. Patent No. 11,893,673 B2.
Instant application claim 3
U.S. Patent No. 11,893,673 B2 – claim 17
3. The method of claim 2 wherein at least one Input Constraint Shape is a Combination Shape corresponding to a combination between the two or more Morph Target Shapes with unitary weights.
17. The method of claim 1 wherein constraint shapes include combination shapes corresponding to a combination between the two or more morph target shapes with unitary weights.
The recitations are substantially identical—both require constraint shapes that are combination shapes corresponding to combinations of morph target shapes with unitary weights. Claim 3 is therefore not patentably distinct from parent claim 17.
Claim 4 is rejected as being obvious in light of claim 21 of U.S. Patent No. 11,893,673 B2.
Instant application claim 4
U.S. Patent No. 11,893,673 B2 – claim 21
4. The method of claim 2 wherein at least one Input Constraint Shape is an Incremental Shape corresponding to a partial weighting of one or more of the Morph Target Shapes.
21. The method of claim 1 wherein constraint shapes include at least one incremental shape corresponding to a partial weighting of one or more of the morph target shapes.
The recitations are substantially identical—both require constraint shapes that are incremental shapes corresponding to a partial weighting of morph target shapes. Claim 4 is therefore not patentably distinct from parent claim 21.
Claim 12 is rejected as being obvious in light of claim 1 of U.S. Patent No. 11,893,673 B2.
Instant application claim 12
U.S. Patent No. 11,893,673 B2 – claim 1
12. A method for generating a weighted interpolation between two or more Control Shapes, at least one of the Control Shapes being a Complex Shape comprising a weighted combination of a plurality of Component Shape, including the steps of: mapping the Control Shapes into their constituent Component Shapes and associated weightings on each of the constituent Component Shapes to form a set of weighted target Component Shapes, wherein each weighted target Component Shape in the set of weighted target Component Shapes has a weight greater than zero; providing the set of weighted target Component Shapes to an Interpolator; using the Interpolator to interpolate between the set of weighted target Component Shapes to generate the weighted interpolation between the two or more Control Shapes.
1. A method for generating a weighted interpolation between a plurality n of morph target shapes B1 . . . Bn relative to a base shape B0 including the steps of: receiving a set of weights W…; receiving a plurality m of constraint shapes C1 . . . Cm, each constraint shape associated with non-zero weights (associated weights) on one or more of the morph target shapes B1 . . . Bn (associated shapes); generating a continuous multivariate interpolation function… and using the weights W to be applied to morph target shapes as arguments of the interpolation function to generate the weighted interpolation…
Parent claim 1's constraint shapes with associated non-zero weights on underlying morph target shapes read on instant claim 12's Control Shapes/Complex Shapes mapped into constituent Component Shapes with associated weightings. The amended "weight greater than zero" limitation is rendered obvious by the parent's "non-zero weights," since blendshape/morph-target weights are conventionally strictly positive in the associated (contributing) case. The parent's multivariate interpolation function using weights as arguments corresponds to the recited Interpolator generating the weighted interpolation.
Claim 17 is rejected as being obvious in light of claim 1 of U.S. Patent No. 11,893,673 B2.
Instant application claim 17
U.S. Patent No. 11,893,673 B2 – claim 1 (relevant portion)
17. The method of claim 12 wherein the mapping of the Control Shapes into at least some of their constituent Component Shapes and associated weightings on each of the constituent Component Shapes is predefined.
1. …receiving a plurality m of constraint shapes C1 . . . Cm, each constraint shape associated with non-zero weights (associated weights) on one or more of the morph target shapes B1 . . . Bn (associated shapes)…
The parent's step of "receiving" constraint shapes together with their associated non-zero weights on morph target shapes encompasses a predefined mapping between each Complex/Control Shape and its constituent Component Shapes with associated weightings. Claim 17 is therefore not patentably distinct from parent claim 1.
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) 2-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wampler (US 20180130256 A1), in view of Ma et al. (US 20180033190 A1, hereinafter Ma) and further in view of Lewis et al. (“Practice and Theory of Blendshape Facial Models”, hereinafter Lewis).
Regarding Claim 2, Wampler teaches a method for generating a weighted interpolation between two or more Morph Target Shapes (Wampler, Paragraph [0052], “the stylized mesh deformation determines the weights for combining the input meshes 102 a-102 e <read on Morph Target Shapes> by utilizing a combined shape-space, deformation interpolation measure.”), the Morph Target Shapes each including a plurality of topologically consistent vertex coordinates (Wampler, Paragraph [0060], “each of the input meshes 202-206 <read on Morph Target Shapes> reflect different configurations of a common digital model defined by a set of vertices <read on vertex coordinates>.”; Wampler, Paragraph [0060], “each of the input meshes 202-206 comprise a plurality of common vertices <read on topologically consistent vertex coordinates> in differ- ent arrangements.”). including the steps of: receiving a plurality of Input Constraint Shapes including a plurality of vertex coordinates topologically consistent with those of the Morph Target Shapes” (Wampler, Paragraph [0060], “each of the input meshes 202-206 <read on Input Constraint Shapes> comprise a plurality of common vertices <read on vertex coordinates topologically consistent with those of the Morph Target Shapes> in differ- ent arrangements.”), each Input Constraint Shape associated with non-zero weights on one or more of the Morph Target Shapes (Wampler, Paragraph [0070], “the stylized mesh deformation system defines the weights 220-224 such that they must be positive <read on non-zero weights> and sum to one (or some other set value).”; Wampler, Paragraph [0070], “the weights 220-224 reflect a relative contribution of each input mesh 202-206 <read on Input Constraint Shapes> to the modified mesh 234.”). generating Additional Constraint Shapes for a plurality of new weightings on Morph Target Shapes using the Input Constraint Shapes, and associating the Additional Constraint Shapes with their respective new weightings (Wampler, Paragraph [0053], “the stylized mesh deformation system can generate modified meshes <read on Additional Constraint Shapes> by variably combining input meshes <read on Input Constraint Shapes> across a digital model.”; Wampler, Paragraph [0053], “the stylized mesh deformation system utilizes a first combination of the input shapes <read on Input Constraint Shapes> IOU and 102e to generate the tail portion 116e of the modified mesh <read on Additional Constraint Shape> 114”; Wampler, Paragraph [0053], “the stylized mesh deformation system utilizes a second combination of the input shapes <read on Input Constraint Shapes> 102a and 102e to generate the neck portion 118e of the modified mesh <read on Additional Constraint Shape> 114”). receiving interpolation weightings for each of the two or more Morph Target Shapes (Wampler, Paragraph [0052], “the stylized mesh deformation system selects weights <read on interpolation weightings> to combine and deform the input meshes 102a-I02e <read on Morph Target Shapes>”), generating an Interpolation Function for interpolating between the two or more Morph Target Shapes (Wampler, Paragraph [0137], “the stylized mesh deformation system can generate an ARAP combined shape-space, deformation interpolation measure <read on Interpolation Function> by generalizing equation 7 to interpolate between multiple input shapes <read on Morph Target Shapes>.”).
But Wampler does not explicitly disclose relative to a Base Shape, wherein the Interpolation Function comprises a first term incorporating a weighted combination of Morph Target Shapes and a second term incorporating a weighted combination of Constraint Shapes, or generating, using the Interpolation Function and using interpolation weightings as arguments to the Interpolation Function, vertex coordinates corresponding to the weighted interpolation between the two or more Morph Target Shapes.
However, Ma teaches the Morph Target Shapes each including a plurality of topologically consistent vertex coordinates (Ma, Paragraph [0015], “each template blendshape <read on Morph Target Shape> is defined by data representative of a plurality of vertices <read on vertex coordinates> and relationships between said vertices <read on topological consistency>”), and generating, using the Interpolation Function and using interpolation weightings as arguments to the Interpolation Function, vertex coordinates corresponding to the weighted interpolation between the two or more Morph Target Shapes (Ma, Paragraph [0125], “the present animation process computes output blendshape coefficients <read on interpolation weightings>”; Ma, Paragraph [0125], “by interpolating input blendshapes <read on Morph Target Shapes> linearly and the closest point on the input mesh for each vertex <read on vertex coordinates> in the interpolated blendshape.”).
Ma and Wampler are analogous since both are directed to generating animated three-dimensional mesh shapes by applying weights to multiple mesh or blendshape inputs. Wampler provides a weight-driven framework that combines and deforms input meshes to generate modified meshes. Ma provides a coefficient-based blendshape model in which component shapes are represented by vertices and their relationships, and input blendshapes are linearly interpolated into an output three-dimensional mesh.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate Ma’s vertex-defined blendshape representation and coefficient-driven linear interpolation into Wampler’s modified-mesh deformation system such that Wampler’s input meshes are implemented as topologically corresponding blendshapes and the resulting weighted interpolation is generated as an output mesh having interpolated vertex coordinates. The motivation is to use Ma’s known blendshape interpolation technique to provide predictable vertex-level output in Wampler’s weight-driven mesh-animation system.
However, the combination does not explicitly disclose but Lewis teaches relative to a Base Shape (Lewis, Section 3.1, “one face model b0 <read on Base Shape> (typically the resting face expression) is designated as the “neutral” face shape, and the remaining targets bk, k =”). receiving a plurality of Input Constraint Shapes including a plurality of vertex coordinates topologically consistent with those of the Morph Target Shapes, each Input Constraint Shape associated with non-zero weights on one or more of the Morph Target Shapes (Lewis, Section 3.3, “Another blendshape variant [Osi07, Ver, ZO14] adds additional “correction” shapes <read on Input Constraint Shapes> that become active to the extent that particular pairs (or triples, etc.) of weights <read on weights on one or more of the Morph Target Shapes> are active.”; Lewis, Section 3.3, “w1 w5 b1,5 is a bilinear “correction” shape <read on Input Constraint Shape> that is fully added only when w1 and w5 are both one <read on non-zero weights>, and is completely off if either is zero.”). generating Additional Constraint Shapes for a plurality of new weightings on Morph Target Shapes using the Input Constraint Shapes, and associating the Additional Constraint Shapes with their respective new weightings (Lewis, Section 3.3, “This scheme is variously called combination blendshapes or corrective shapes <read on Additional Constraint Shapes> [ZO14].”; Lewis, Section 3.3, “The combination targets <read on Additional Constraint Shapes> are situated at (some of) the diagonals of the blendshape hypercube”; Lewis, Section 3.2, “as that in Maya [Tic09] allow targets <read on Additional Constraint Shapes> to be situated at intermediate weight values <read on new weightings>, giving piecewise linear interpolation.”). generating an Interpolation Function for interpolating between the two or more Morph Target Shapes using the Base Shape, [[Input Constraint Shapes]] and Additional Constraint Shapes, wherein the Interpolation Function comprises a first term incorporating a weighted combination of Morph Target Shapes and a second term incorporating a weighted combination of Constraint Shapes (Lewis, Section 3.1, “one face model b0 <read on Base Shape> (typically the resting face expression) is designated as the “neutral” face shape, and the remaining targets bk <read on Morph Target Shapes>, k = 1 . . .n are replaced with the difference bk− b0 between the”); (Lewis, Section 3.3, “Another blendshape variant [Osi07, Ver, ZO14] adds addi-tional “correction” shapes <read on Additional Constraint Shapes> that become active to the extent that particular pairs (or triples, etc.) of weights are active. This scheme is variously called combination blendshapes orcorrective shapes <read on Constraint Shapes> [ZO14].”); and (Lewis, Section 3.3, “This approach might be notated as f = f0 <read on Base Shape> + w1b1 + w2b2 + w3b3 +···w1 w5 b1,5 + w2 w13 b2,13 +···w2 w3 w10 b2,3,10 +···”). wherein the Interpolation Function comprises a first term incorporating a weighted combination of Morph Target Shapes (Lewis, Section 3.1, “kth face target <read on Morph Target Shape> and the neutral face: f = b0 <read on Base Shape> + n∑k=1 wk <read on interpolation weighting>(bk <read on Morph Target Shape>− b0) (3) (with b0 being the neutral shape).”); and (Lewis, Section 3.3, “This approach might be notated as f = f0 <read on Base Shape> + w1 <read on interpolation weighting>b1 <read on Morph Target Shape> + w2 <read on interpolation weighting>b2 <read on Morph Target Shape> + w3 <read on interpolation weighting>b3 <read on Morph Target Shape> +··· w1 w5 b1,5 + w2 w13 b2,13 +··· w2 w3 w10 b2,3,10 +···”). The first line of Lewis’s latter equation includes w1b1+w2b2+w3b3+⋯w1b1+w2b2+w3b3+⋯. In the context of Lewis’s preceding identification of bkbk as the “kth face target” and wkwk as the variable in its weighted blendshape equation, this is the claimed first term incorporating a weighted combination of Morph Target Shapes. a second term incorporating a weighted combination of Constraint Shapes (Lewis, Section 3.3, “Another blendshape variant [Osi07, Ver, ZO14] adds additional “correction” shapes that become active to the extent that particular pairs (or triples, etc.) of weights are active. This scheme is variously called combination blendshapes or corrective shapes <read on Constraint Shapes>”); (Lewis, Section 3.3, “This approach might be notated as f = f0 + w1b1 + w2b2 + w3b3 +··· w1 <read on interpolation weighting> w5 <read on interpolation weighting> b1,5 <read on Constraint Shape> + w2 <read on interpolation weighting> w13 <read on interpolation weighting> b2,13 <read on Constraint Shape> +···w2 <read on interpolation weighting> w3 <read on interpolation weighting> w10 <read on interpolation weighting> b2,3,10 <read on Constraint Shape> +···”); and (Lewis, Section 3.3, “w1 w5 b1,5 <read on Constraint Shape> is a bilinear “correction” shape that is fully added only when w1 and w5 are both one, and is completely off if either is zero.”; it is noted the latter two lines of equation are separately weighted correction/combination-shape contributions. Lewis expressly identifies b1,5b1,5 as a “correction” shape and states that it is fully added when w1w1 and w5w5 are both one. Thus, the equation’s latter two lines provide the claimed second term incorporating a weighted combination of Constraint Shapes).
Lewis and the Wampler–Ma combination are analogous since all are directed to computer-animation systems that create interpolated three-dimensional mesh deformations from weighted shape components. Wampler provides weighted mesh deformation across multiple input meshes. Ma provides coefficient-based blendshape interpolation and output mesh vertices. Lewis provides a known base-plus-primary-blendshape-plus-correction-shape function for handling interactions among multiple active shape weights. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate Lewis’s neutral-base and correction/combination-blendshape architecture into the modified Wampler–Ma mesh interpolation system such that the interpolation function includes a Base Shape, a first weighted Morph Target Shape term, and a second weighted Constraint Shape term. The motivation is to improve the fidelity of interpolated shapes when multiple weights are active, because Lewis teaches that correction shapes become active when particular combinations of primary-shape weights are active.
Regarding Claim 3, the combination of Wampler, Ma and Lewis teaches the invention in Claim 2.
The combination further teaches wherein at least one Input Constraint Shape is a Combination Shape corresponding to a combination between the two or more Morph Target Shapes with unitary weights (Wampler, Paragraph [0053], combination of the input shapes 102d and 102e to generate the tail portion 116c of the modified mesh 114 (e.g., combines vertices from the tail portion 116a from the input shape 102d and vertices from the tail portion 116b from the input shape 102e based on a first set of weights to generate the tail portion 116c). Similarly, the stylized mesh deformation system utilizes a second combination of the input shapes 102a and 102c to generate the neck portion 118c of the modified mesh); [0058], input mesh deformation interpolation measure” refers to a weighted quantification of deformation of all or a portion of vertices in a plurality input meshes).
Regarding Claim 4, the combination of Wampler, Ma and Lewis teaches the invention in Claim 2.
The combination further teaches wherein at least one Input Constraint Shape is an Incremental Shape (Wampler, Paragraph [0062], the stylized mesh deformation system generates modified meshes that smoothly and gradually transition between the input meshes 202-206. In particular, the stylized mesh deformation system gradually combines the input meshes 202-206 to generate the modified meshes [0082], the stylized mesh deformation system can operate in conjunction with nonphysical shapes or simulated physical shapes) corresponding to a partial weighting of one or more of the Morph Target Shapes (Wampler, Paragraph [0062], the stylized mesh deformation system generates modified meshes that smoothly and gradually transition between the input meshes. [0057], a portion of a mesh generated by a blending algorithm that blends input shapes within a shape space according to one or more weights. [0070], the stylized mesh deformation system defines the weights 220-224 such that they must be positive and sum to one (or some other set value)).
Claim(s) 5-6, 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wampler (US 20180130256 A1), in view of Ma et al. (US 20180033190 A1, hereinafter Ma) and further in view of Lewis et al. (“Practice and Theory of Blendshape Facial Models”, hereinafter Lewis) as applied to Claim 1 above and further in view of Chen et al. (US 20190139277 A1, hereinafter Chen).
Regarding Claim 5, the combination of Wampler, Ma and Lewis teaches the invention in Claim 2.
The combination does not explicitly disclose but Chen teaches wherein the additional Constraint Shapes are generated at new weightings such as to complete or augment an n-dimensional cube (Chen, Paragraph [0041], As used herein, the term “cell” refers to a three-dimensional digital shape (e.g., a cube) that forms a portion of a digital cage; [0159], determines and employs one or more deformation weights to modify bristle vertices to new spatial locations within a deformed digital cage) wherein Morph Target Shapes are dimensions of the n-dimensional cube having the Base Shape as the origin and edges of the n-dimensional cube as weightings on Morph Target Shapes (Chen, Paragraph [0041], As used herein, the term "cell" refers to a three-dimensional digital shape ( e.g., a cube) that forms a portion of a digital cage… a cell includes a three-dimensional cube that encompasses a subset of bristle vertices from a subset of bristles in a digital brush. Indeed, each portion of a bristle that passes through a cell can include one or more bristle vertices located within the cell. In addition, each cell can include cell vertices, such as corners of the cell where three or more edges meet).
Chen and Wampler are analogous since both of them are dealing with of shapes deformation in 3D modeling. Wampler provided a way of using multiple shapes deformation using continuously weighted shape blending in the 3D modelling.
Chen provided a way of using spatial location of a cube object vertex change to updating the weight for deformation during the 3D modelling. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate interpolation of weight changes taught by Chen into modified invention of Wampler such that during the 3D modelling, system will be able to generalize cube/weight deformation framework to higher dimensional weight
spaces when interpolating among multiple morph target dimensions. The motivation is to allow underlying operation to apply independent weights along independent degrees of freedom to generate new constrained shapes with more realistic result.
Regarding Claim 6, the combination of Wampler, Ma, Lewis and Chen teaches the invention in Claim 5.
The combination further teaches wherein additional Constraint Shapes are generated using a meshless interpolation method (Chen, Paragraph [0072], the brush deformation system models deformation of digital cages utilizing the approach for deforming three-dimensional objects described by Matthias Müller, Bruno Heidelberger, Matthias Teschner, and Markus Gruss in Meshless Deformations Based on Shape Matching).
Chen and Wampler are analogous since both of them are dealing with of shapes deformation in 3D modeling. Wampler provided a way of using multiple shapes deformation using continuously weighted shape blending in the 3D modelling. Chen provided a way of using spatial location of a cube object vertex change to updating the weight for deformation during the 3D modelling using Meshless deformation. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate generation of additional constraint shapes using the meshless deformation approach taught by Chen into modified invention of Wampler such that during the 3D modelling, system will be able to model deformation using a meshless deformation approach (Meshless Deformations Based on Shape Matching) in order to track weight changing of edges of cubed object in to precisely updating the modeling result using meshless deformation which increase the flexibility of the modelling system.
Regarding Claim 8, the combination of Wampler, Ma and Lewis teaches the invention in Claim 2.
The combination further teaches including the step of partitioning the n-dimensional cube into lower dimensional spaces and generating additional Constraint Shapes for each lower dimensional space (Wampler, Paragraph [0083], the shape of the sth input mesh, denoted by p.sub.s, is represented with a one-dimensional array of length |custom-character|, each element of which is a k-dimensional vector describing the position of a single vertex, where k is either two or three depending on the dimension of the space the mesh).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wampler (US 20180130256 A1), in view of Ma et al. (US 20180033190 A1, hereinafter Ma) and further in view of Lewis et al. (“Practice and Theory of Blendshape Facial Models”, hereinafter Lewis) and Chen et al. (US 20190139277 A1, hereinafter Chen) as applied to Claim 6 above and further in view of Su et al. (US 20140064588 A1, hereinafter Su)
Regarding Claim 7, the combination of Wampler, Ma, Lewis and Chen teaches the invention in Claim 6.
The combination further teaches wherein additional Constraint Shapes are generated using [[ radial basis ]] interpolation (Wampler, Paragraph [0034], an “input mesh deformation interpolation measure”) and (2) an amount of deformation of a blended mesh generated in a shape space defined by the input meshes to satisfy input constraints) .
The combination does not explicitly disclose the generation is using radial basis interpolation.
However, Su teaches shapes are generated using radial basis interpolation (Su, Paragraph [0009], the step of forming the morphed meshes uses one of the input meshes as a generic mesh, and for each of the other input meshes forms the corresponding morphed mesh by deforming the generic mesh to the shape of the other input mesh. The deformation of the generic mesh can be performed using a radial basis function (RBF) morphing).
Su and Wampler are analogous since both of them are dealing with of shapes deformation in 3D modeling. Wampler provided a way of using multiple shapes deformation using continuously weighted shape blending in the 3D modelling. Su provided a way of using radial basis interpolation during the 3D modelling. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate RBF morphing as a known interpolation technique for generating intermediate/deformed meshes from input meshes taught by Su into modified invention of Wampler such that during the 3D modelling, system will be able to using a radial basis function (RBF) approach with progressive projection coupled with local smoothing in generation of additional constraint shapes in the combined system to crate predictable results with a reasonable expectation of success to ensure robustness.
Claim 9, 11, 15, 16 is/are rejected under 35 U.S.C. § 103 as being unpatentable over Ma et al. (US 20180033190 A1, hereinafter Ma) in view of Bouaziz et al. (US 20140362091 A1, hereinafter Bouaziz).
Regarding Claim 9, Ma teaches A method for estimating underlying Component Shape weights of a Complex Shape including the steps of (Ma, Paragraph [0075], "In the blendshape personalization and optimization process, a set of template blendshapes are personalized and optimized relative to facial expression measurements, taken from actor performances, to yield output blendshapes that are sufficiently close reproductions of the original facial expressions"; the blendshape weights w_i solved by the optimization <read on Component Shape weights> and the reconstructed face pose x_i <reads on Complex Shape>), receiving one or more suggested Component Shapes (Ma, Paragraph [0080], "An initial blendshape model is created using deformation transfer, as shown in 302, which is known in the art. Each synthesized expression bi for the subject is generated by applying the deformation gradients from a source character pose to b0 (initial pose)"; it is noted the acquired template blendshapes/synthesized expressions b_i supplied to the optimizer <read on suggested Component Shapes>); and [[obtaining Component Shape weights through ]] solving least square problem [[ where penalties and ]] Solution Boundaries are enforced to ensure the weights of suggested Component Shapes are greater than zero (Ma, Paragraph [0085], "the L1 regularization problem is turned into a constrained least squares problem, which can be solved with any quadratic programming solver" <reads on solving least square problem>), (Ma, Paragraph [0081], "The weights wi are constrained between 0.0 and 1.0." <reads on Solution Boundaries are enforced>), (Ma, Paragraph [0088], "Taking advantage that the weight wi is non-negative" <reads on the weights of suggested Component Shapes are greater than zero>).
But Ma does not explicitly disclose obtaining Component Shape weights through solving least square problem where penalties … are enforced as an explicit additive penalty term formulated on the Component Shape weight/coefficient vector inside the least-squares objective.
However, Bouaziz teaches obtaining Component Shape weights through solving least square problem where penalties … are enforced (Bouaziz, Paragraph [0080], "This may yield a fitting energy of the form Efit=∥A(b0+ΔBx)−c∥2 2"; the squared-norm data-fitting term E_fit on the blendshape weight vector x <reads on solving least square problem>), (Bouaziz, Paragraph [0080], "The optimization may iteratively minimize the following energy according to Equation (1): arg min_x E_fit + λ_1 E_smooth + λ_2 E_sparse. (1) Accordingly, two additional terms, Esmooth and Esparse with non-negative weights λ1 and λ2, may be added for regularization <reads on penalties … are enforced>"), (Bouaziz, Paragraph [0080], "Temporal smoothness may be enforced by penalizing the second-order difference Esmooth=∥xt-2−2xt-1+xt∥2 2"; an additive term formulated on the blendshape coefficient vector x <read on Component Shape weights of suggested Component Shapes> that penalizes departures from the previous-frame coefficients <reads on penalties … are enforced>), (Bouaziz, Paragraph [0081], "the 1-norm regularization Esparse=∥x∥1 on the blendshape coefficients may be applied"; a further additive 1-norm regularization term formulated on the blendshape coefficient vector x <reads on penalties … are enforced>).
Bouaziz and Ma are analogous since both deal with facial-animation systems that compute blendshape (Component Shape) coefficients/weights to reconstruct an input facial pose (Complex Shape) by minimizing a fitting-error objective over a template basis of blendshapes. Ma provided a way of computing blendshape weights w_i by solving a constrained least-squares fit with box bounds and non-negativity, so the enforcement of Solution Boundaries and the greater-than-zero requirement on the weights are already carried by Ma itself. Bouaziz provided a way of solving for the blendshape weights x by iteratively minimizing a total energy in which explicit additive regularization terms are formulated directly on the blendshape coefficient vector with non-negative weights. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate Bouaziz's additive coefficient-vector regularization terms into the modified invention of Ma such that the constrained least-squares blendshape solve of Ma carries — in addition to its box-bound and non-negativity constraints — one or more explicit additive penalty terms formulated on the Component Shape weight vector. The motivation is that the 1-norm regularization "may stabilize the tracking, since the blendshape basis is not linearly independent" and "favours a reconstruction with as few blendshapes as possible in order to avoid potential blendshape compensation artefacts and better match the blendshape weights a human animator would typically choose," as discussed by Bouaziz in Paragraph [0081], and to enforce temporal smoothness by "penalizing the second-order difference" between consecutive-frame coefficient vectors, as discussed by Bouaziz in Paragraph [0080].
Regarding Claim 11, the combination of Ma and Bouaziz teaches the invention in Claim 9.
The combination further teaches wherein underlying Component Shape weights are estimated on a lower dimensional space (Ma, Paragraph [0077], "even if the head rigid motion and neutral pose are set as constant, Equation 2 simply becomes a matrix factorization problem"; the matrix factorization P̃ ≈ D·W in which the solved coefficient matrix W (indexed by n_b blendshape components) has dimension far smaller than the vertex-space representation P̃ (indexed by 3·n_v vertices) <reads on estimated on a lower dimensional space>), (Ma, Paragraph [0082], "the weights can be solved with constrained quadratic programming when R and t are fixed"; the constrained QP is posed on the blendshape weight vector w_i whose dimension n_b is a lower-dimensional coefficient space compared to the 3·n_v vertex-space of x_i <reads on estimated on a lower dimensional space>).
Regarding Claim 15, the combination of Ma and Bouaziz teaches the invention in Claim 9.
The combination further teaches wherein Complex Shapes represent one or more of the group consisting of: emotional expressions, visemes and facial expressions unique to an individual (Ma, Paragraph [0075], " n the blendshape personalization and optimization process, a set of template blendshapes are personalized and optimized relative to facial expression measurements, taken from actor performances, to yield output blendshapes that are sufficiently close reproductions of the original facial expressions"; the output "personalized" blendshapes that reproduce the actor's own facial expressions <read on facial expressions unique to an individual>, which is one member of the recited "one or more of the group"), (Ma, Paragraph [0004], "Various expressions, such as smiling, laughing, frowning, growling, yelling, closed eyes, open eyes, heightened eyebrows, lowered eyebrows, pursed lips, and mouth shapes of vowels or consonants, blend or morph into the base shape and, in so doing, are referred to as blendshapes or morph targets"; the recited "smiling, laughing, frowning, growling, yelling" <read on emotional expressions>, and the recited "mouth shapes of vowels or consonants" — i.e., the visual representations of phonemic mouth positions during speech — <read on visemes>); (Ma, Paragraph [0060], "measurements of various facial movements and expressions of an individual are made"; the facial expressions of an individual person captured and reconstructed <read on facial expressions unique to an individual>).
Regarding Claim 16, the combination of Ma and Bouaziz teaches the invention in Claim 9.
The combination further teaches wherein Component Shapes represent FACS action units (Ma, Paragraph [0007], "this collection of blendshapes is usually designed to isolate muscle group action units according to the Facial Action Coding System (FACS)"; the blendshapes used by Ma's optimization solver are the collection of blendshapes that isolate muscle group action units of FACS <reads on Component Shapes represent FACS action units>).
Claim 10 is rejected under 35 U.S.C. § 103 as being unpatentable over Ma et al. (US 20180033190 A1, hereinafter Ma) in view of in view of Bouaziz et al. (US 20140362091 A1, hereinafter Bouaziz) as applied to Claim 9 above and further in view of Weise et al. (US 20190139287 A1, hereinafter Weise).
Regarding Claim 10, the combination of Ma and Bouaziz teaches the invention in Claim 9.
The combination does not explicitly disclose but Weise teaches wherein the method includes the step of receiving weights for at least one but not all of the suggested Component Shapes and using the received weights to restrict the solution to the least square problem problem (Weise, Paragraph [0026], "The method may comprise the step of storing these animation sequences to define an animation prior. The animation sequences may be defined by expression parameters"; and (Weise, Paragraph [0028], "The method may further comprise the step of representing the expression parameters as a series of blendshape weights"; the stored animation-prior sequences of blendshape weights covering only the predefined animation subset of the whole blendshape library <read on receiving weights for at least one but not all of the suggested Component Shapes>), (Weise, Paragraph [0019], "performing a single optimization calculation using the animation priors and the 2D image and 3D depth map of face of the user, to determine the expression parameters required to update the user-specific expression model"; the single optimization calculation minimizes a sum-of-squared-error objective (E_geo of squared point-plane distances plus E_im of squared image-gradient distances) <reads on the least square problem>, and the animation priors (received blendshape weights) are folded directly into that minimization <reads on using the received weights to restrict the solution to the least square problem>), (Weise, Paragraph [0019], " performing a single optimization calculation using the animation priors and the 2D image and 3D depth map of face of the user, to determine the expression parameters required to update ed to prevent unrealistic face poses"; the received prior acting as a regularizer that narrows the feasible region of the sum-of-squared-error solve <reads on using the received weights to restrict the solution to the least square problem>).
Weise and Ma are analogous since all deal with facial-animation systems that solve for blendshape (Component Shape) weights via an optimization framework. Ma provided a way of solving for blendshape weights via a constrained least-squares fit with penalties and box bounds. Weise provided a way of receiving predefined/stored blendshape weights and folding them into the solve as a prior that restricts the optimization. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate Weise's received-prior-weights technique into the modified invention of Ma such that the constrained least-squares solve accepts received blendshape weights for a proper subset of the suggested Component Shapes and uses them to restrict the solve for the remaining weights. The motivation is to "prevent unrealistic face poses" as discussed by Weise in Paragraph [0020].
Claim 12, 17-20 is rejected under 35 U.S.C. § 103 as being unpatentable over Li et al., “Example-Based Facial Rigging,” in view of Ma et al. (US 2018/0033190 A1), and further in view of Wampler (US 2018/0130256 A1).
Regarding Claim 12, Li teaches A method for generating a weighted interpolation between two or more Control Shapes, at least one of the Control Shapes being a Complex Shape comprising a weighted combination of a plurality of Component Shape, including the steps of: (Li, Page 3, “We assume a generic blendshape model is given as a set of meshes A ={A0,...,A n}, where A0 is the rest pose and the Ai <read on Component Shapes>,i >0 are additive displacements. Expressions can be generated as Tj <read on Control Shapes> = A0 + ∑n i=1αij <read on associated weightings>Ai <read on Component Shapes>, whereαij are the blending weights of poseTj.”).
mapping the Control Shapes into their constituent Component Shapes and associated weightings on each of the constituent Component Shapes to form a set of weighted target Component Shapes (Li, Page 3, “Our goal is to compute a new blendshape model B = {B0,...,B n} that matches the geometry and motion of the actor.”; Li, Page 3, “Thus we need to find blendshapes Bi <read on constituent Component Shapes> and corresponding weightsαij <read on associated weightings> such that the training poses Sj <read on Control Shapes> are faithfully reproduced”). [[wherein each weighted target Component Shape in the set of weighted target Component Shapes has a weight greater than zero;]] [[providing the set of weighted target Component Shapes to an Interpolator;]] [[using the Interpolator to interpolate between the set of weighted target Component Shapes to generate the weighted interpolation between the two or more Control Shapes.]]
But Li does not explicitly disclose wherein each weighted target Component Shape in the set of weighted target Component Shapes has a weight greater than zero,” “providing the set of weighted target Component Shapes to an Interpolator,” or “using the Interpolator to interpolate between the set of weighted target Component Shapes to generate the weighted interpolation between the two or more Control Shapes.
However, Ma teaches providing the set of weighted target Component Shapes to an Interpolator (Ma, Paragraph [0125], “Starting from an initial guess of the coefficients <read on associated weightings> of the applicable blendshapes <read on weighted target Component Shapes> for a given frame, which can be a neutral shape (a coefficient of 1 for neutral and 0 for other shapes) or imported from prior calculations, the present animation process computes output blendshape coefficients by engaging in a first correspondence process 1001 and an iterative coefficient update process 1002, 1003, 1004a-c.”).
using the Interpolator to interpolate between the set of weighted target Component Shapes to generate the weighted interpolation between the two or more Control Shapes” (Ma, Paragraph [0125], “a blendshape is associated with the 3d dense stereo reconstruction, also referred to as a 3d mesh, by interpolating input blendshapes <read on weighted target Component Shapes> linearly and the closest point on the input mesh for each vertex in the interpolated blendshape.”). [[wherein each weighted target Component Shape in the set of weighted target Component Shapes has a weight greater than zero.]]
Ma and Li are analogous since both are directed to facial-animation systems that generate facial-expression meshes from weighted blendshape components. Li provides target blendshape components and corresponding component weights for reproducing facial-expression poses. Ma provides a coefficient-based linear blendshape interpolation process that produces an interpolated three-dimensional mesh.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate Ma’s linear blendshape interpolation process into Li’s target blendshape-model procedure in order to generate a three-dimensional output mesh from Li’s target blendshape components and their corresponding weights. The motivation is to use Ma’s known coefficient-based interpolation process to provide a direct and predictable mesh-generation operation for Li’s target facial-expression model.
But the combination does not explicitly disclose wherein each weighted target Component Shape in the set of weighted target Component Shapes has a weight greater than zero.
However, Wampler teaches wherein each weighted target Component Shape in the set of weighted target Component Shapes has a weight greater than zero (Wampler, Paragraph [0070], “the stylized mesh deformation system definesthe weights 220-224 <read on associated weightings> such that they must be positive <read on greater than zero> and sum to one (or some other set value).”; Wampler, Paragraph [0070], “the weights 220-224 reflect a relative contri-bution of each input mesh 202-206 <read on weighted target Component Shapes> to the modified mesh 234.”).
Wampler and the Li–Ma combination are analogous since each is directed to weighted interpolation or deformation of multiple three-dimensional mesh shapes. Li and Ma provide weighted blendshape components and linear interpolation of those components. Wampler provides a positive-weight constraint under which each input mesh contributes to the generated modified mesh.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate Wampler’s positive-weight constraint into the modified Li–Ma blendshape interpolation system in order to ensure that each Component Shape intentionally included in the weighted target Component Shape set has a positive associated weight. The motivation is to retain the contribution of every Component Shape included in the selected target set during interpolation, rather than permit a zero-weight value to exclude a selected shape from the generated output.
Regarding Claim 17, the combination of Li, Ma, and Wampler teaches the invention of Claim 12.
The combination further teaches wherein the mapping of the Control Shapes into at least some of their constituent Component Shapes and associated weightings on each of the constituent Component Shapes is predefined (Li, Page 2, “we propose to use a predefined generic blendshape rig <read on predefined> as a semantic prior.”; Li, Page 3, “For this purpose, the user selects ap-propriate blending weights <read on associated weightings> on the template <read on Control Shapes> to model a poseTj that roughly corresponds to the training pose Sj.”).
Li teaches a predefined generic blendshape rig that provides template blendshape semantics before construction of the target model. Li further teaches selection of template blending weights used to model a corresponding training pose. Thus, Li teaches a predefined mapping of at least some Control Shapes into Component Shapes and associated weightings. Li and the Ma–Wampler combination are analogous since each concerns weighted animation models using plural component shapes. Li provides a predefined generic blendshape rig and template-associated blending weights. Ma and Wampler provide respective weighted blendshape interpolation and weighted mesh deformation techniques. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to use Li’s predefined generic blendshape rig and template blending weights in the Li–Ma–Wampler interpolation system in order to provide a predefined component-shape mapping for at least some animation controls. The motivation is to preserve the controller semantics of the predefined generic blendshape rig during target-model generation.
Regarding Claim 18, the combination of Li, Ma, and Wampler teaches the invention of Claim 12.
The combination further teaches wherein the generated weighted interpolation is to be visualized on an end user display device of an electronic computing device (Ma, Paragraph [0015], “discloses a computer-implemented method for generatingand dynamically modifying a blendshape within a graphical user interface rendered in a display <read on end user display device>, said method being implemented in a computer <read on electronic computing device>; Ma, Paragraph [0015], “wherein said computer is in data communication with the display <read on end user display device> and with a storage unit”).
Ma and the Li–Wampler combination are analogous since each concerns generating weighted mesh or blendshape outputs in a computer-animation system. Li and Wampler provide weighted shape components and weighted mesh generation. Ma provides a computer-implemented blendshape process having a graphical user interface rendered in a display.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to provide the generated weighted interpolation of the Li–Ma–Wampler system to Ma’s graphical display interface in order to permit an end user to view the generated facial-animation mesh. The motivation is to provide visual feedback of the generated blendshape output in Ma’s display-based computer-animation environment.
Regarding Claim 19, the combination of Li, Ma, and Wampler teaches the invention of Claim 12.
The combination further teaches wherein each of the steps is executed on an electronic computing device (Ma, Paragraph [0015], “discloses a computer-implemented method <read on each of the steps is executed on an electronic computing device> for generating and dynamically modifying a blendshape”; Ma, Paragraph [0015], “said method being implemented in a computer <read on electronic computing device> having a minimum clock speed of 2.6 GHz and a minimum random access memory of 2 gigabytes”).
Ma and the Li–Wampler combination are analogous since each concerns computer-executed animation or mesh-processing operations. Li provides generation of target blendshape models and associated weights. Wampler provides weighted mesh deformation. Ma provides a computer-implemented blendshape method.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to execute the Li–Ma–Wampler weighted interpolation procedure on Ma’s computer-implemented animation system in order to perform the blendshape and mesh-processing operations electronically. The motivation is to use Ma’s computer implementation to execute the weighted blendshape interpolation and output-mesh generation operations.
Regarding Claim 20, the combination of Li, Ma, and Wampler teaches the invention of claims 19.
The combination further teaches wherein the generated weighted interpolation is displayed (Ma, Paragraph [0015], “discloses a computer-implemented method for generating and dynamically modifying a blendshape within a graphicaluser interface rendered in a display <read on displayed>”; Ma, Paragraph [0015], “wherein each template blendshape is defined by data representative of a plurality of vertices and relationships between said vertices that, when rendered onto said display <read on displayed>, visually represent at least one facial expression;”).
Ma and the Li–Wampler combination are analogous since each concerns producing weighted animation shapes for display in a computer-based animation environment. Li provides weighted target blendshape components. Wampler provides weighted mesh deformation. Ma provides rendering of a blendshape in a graphical user interface rendered in a display. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to display the generated weighted interpolation of the Li–Ma–Wampler system in Ma’s display-based blendshape interface in order to allow a user to view the resulting facial-expression mesh. The motivation is to present the generated animation output to the user in the graphical interface used for the blendshape process.
Claim 14 is rejected under 35 U.S.C. § 103 as being unpatentable over Li in view of Ma and Wampler, as applied to claim 12 above, and further in view of Stark and Parker, “Bounded-Variable Least-Squares: an Algorithm and Applications.”
Regarding Claim 14, the combination of Li, Ma, and Wampler teaches the invention of Claim 12.
The combination further teaches wherein the step of mapping the one or more Complex Shapes into their constituent Component Shapes includes estimating underlying Component Shape weights of a Complex Shape including the steps of: (Li, Page 3, “Our goal is to compute a new blendshape model B = {B0,...,B n} <read on Complex Shape> that matches the geometry and motion of the actor.”; Li, Page 3, “Thus we need to find blendshapes Bi <read on Component Shapes> and corresponding weights αij <read on Component Shape weights> such that the training poses are faithfully reproduced”). receiving one or more suggested Component Shapes (Li, Page 3, “We assume a generic blendshape model <read on suggested Component Shapes> is given as a set of meshes A ={A0,...,A n}”), and “obtaining Component Shape weights [[through solving least square problem where penalties and Solution Boundaries are enforced to ensure the weights associated with suggested Component Shapes are nonzero]]” (Li, Page 3, “step B keeps blendshapes <read on Component Shapes> fixed and solves for the optimal weights <read on Component Shape weights>.”). obtaining Component Shape weights through solving least square problem where penalties [[and Solution Boundaries are enforced to ensure the weights associated with suggested Component Shapes are nonzero]] (Li, Page 2, “We ensure semantically correct transfer of expressions using additional per vertex regularization weights <read on penalties> in our optimization”; Li, Page 3, “This yields (approxi-mate) weightsα∗ij that provide initial values for step A of the opti- mization and semantic constraints <read on penalties> for step B.”).
But the combination does not explicitly disclose obtaining Component Shape weights through solving least square problem where penalties and Solution Boundaries are enforced to ensure the weights associated with suggested Component Shapes are nonzero.
However, StarkParker teaches obtaining Component Shape weights through solving least square problem where [[penalties and]] Solution Boundaries [[are enforced to ensure the weights associated with suggested Component Shapes are nonzero]]” (StarkParker, Summary, “The Fortran subroutine BVLS (bounded variable least-squares) solves linear least-squares problems with upper and lower bounds <read on Solution Boundaries> on the variables”), and (StarkParker, Page 2, “BVLS (bounded-variable least-squares) is modelled on NNLS and solves the problem bvls: min l≤ x≤ u <read on Solution Boundaries>∥Ax − b∥2 (1)”).
StarkParker and the Li–Ma–Wampler combination are analogous since each concerns determining constrained weights for component representations. Li, Ma, and Wampler provide a facial-animation system using weighted component shapes, positive weights, and interpolation of those shapes. StarkParker provide a bounded-variable least-squares technique that assigns lower and upper boundaries to individual solution variables. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate Stark and Parker’s bounded-variable least-squares technique into Li’s component-weight optimization in order to use lower and upper Solution Boundaries for the component-weight variables. The motivation is to constrain the weight solution within a selected feasible range while retaining Li’s regularization and Wampler’s positive-weight condition.
But the combination does not explicitly disclose “penalties” or “are enforced to ensure the weights associated with suggested Component Shapes are nonzero.”
However, Wampler teaches obtaining Component Shape weights through solving least square problem where penalties and Solution Boundaries are enforced to ensure the weights associated with suggested Component Shapes are nonzero” insofar as Wampler teaches the required nonzero-weight condition (Wampler, Paragraph [0070], “the stylized mesh deformation system defines the weights 220-224 <read on Component Shape weights> such that they must be positive <read on nonzero> and sum to one (or some other set value).”).
Wampler and the Li–Ma–StarkParker combination are analogous since each concerns applying weights to multiple shape components to generate an output shape. Li and Ma provide blendshape components and optimization/interpolation of associated weights. StarkParker provide lower and upper solution boundaries. Wampler provides a positive-weight requirement for weights associated with each input mesh.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to apply Wampler’s positive-weight constraint to the bounded-variable least-squares process of Stark and Parker, as used with Li’s regularized component-weight optimization, in order to prevent any selected Component Shape from receiving a zero weight. The motivation is to preserve each selected Component Shape’s contribution to the target Complex Shape rather than allow a zero-valued solution to eliminate that selected component.
Response to Arguments
The rejection of Claims 2, (3, 17). under Nonstatutory Double Patenting are maintained. In order to overcome the rejection, suggesting applicant to file eTerminal/Terminal Disclaimer.
Applicant’s arguments with respect to claim 2, 9, 12, filed on 6/29/2026, with respect to rejection under 35 USC § 103 in regard to prior art does not teaches the limitation(s) “interactive computer simulation environment" have been considered but are moot in view of the new ground(s) of rejection.
In regard to Claims 3-8, 10-11, 14-20, they directly/indirectly depends on independent Claim 1, 9, 12 respectively. Applicant does not argue anything other than the independent claim 1, 9, 12. The limitations in those claims in conjunction with combination previously established as explained.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20090262118 A1 METHOD, SYSTEM AND STORAGE DEVICE FOR CREATING, MANIPULATING AND TRANSFORMING ANIMATION
US 20180033190 A1 Systems and Methods for Automating the Animation of Blendshape Rigs
US 20180130256 A1 GENERATING EFFICIENT, STYLIZED MESH DEFORMATIONS USING A PLURALITY OF INPUT MESHES
US 20190035149 A1 METHODS OF GENERATING PERSONALIZED 3D HEAD MODELS OR 3D BODY MODELS
US 20190130628 A1 Joint audio-video facial animation system
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/YuJang Tswei/Primary Examiner, Art Unit 2614
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