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 .
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character is not mentioned in the description: 604 (Training Data).
Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 claims 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.
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Claims 1-3, 5, 8, 9, 11, 13, 16 and 18-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-3, 7, 9-12 and 17-20 of co-pending Application No. 18/936217 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because the notion of the claims does refer to the same invention and claims 1-3, 5, 8, 9, 11, 13, 16 and 18-20 or the current application correspond with claims 1-3, 7, 9-12 and 17-20 of co-pending Application No. 18/936217 (respectively). Claims 1-3, 5, 8, 9, 11, 13, 16, 19, 18 and 20 of co-pending Application No. 18/936217 anticipates claims 1-3, 7, 9-12 and 17-20 (respectively) of the current application because it includes all limitations of the current application. The tables below show the claim mapping between the instant/current application 18/936207 and the copending application 18/936217.
18936207
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18936217
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18936207
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18936207
18936217
A computer-implemented method for generating a motion for a virtual character, comprising:
A computer-implemented method for generating a motion for a virtual character, comprising:
determining a graph representation of a plurality of sets of joints corresponding to a sequence of poses for the virtual character based on (i) one or more input poses for the virtual character and (ii) a set of constraints associated with one or more joints included in the plurality of sets of joints;
determining a graph representation of a plurality of sets of joints corresponding to a sequence of poses for the virtual character based on (i) a base motion associated with the sequence of poses and (ii) a set of constraints associated with one or more joints included in the plurality of sets of joints;
generating, via execution of a first neural network, a set of updated node states for the plurality of sets of joints based on the graph representation;
generating, via execution of a first neural network, a set of updated node states for the plurality of sets of joints based on the graph representation;
generating, based on the set of updated node states, the motion that includes (i) a first set of joint positions for the plurality of sets of joints and (ii) a first set of joint orientations for the plurality of sets of joints.
generating, based on the set of updated node states, the motion that includes (i) a first set of joint positions for the plurality of sets of joints and (ii) a first set of joint orientations for the plurality of sets of joints.
Co-pending claims 1-3, 7, 9-12 and 17-20 recite each of the limitations (or a trivial variation) of the current claims 1-3, 5, 8, 9, 11, 13, 16 and 18-20 (respectively) except for the currently-claimed “(i) one or more input poses for the virtual character,” which would be obvious in a combination with Cashman et al. (US 20230326135 A1)”
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, 5, 6, 9, 11-13, 15, 16, and 19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Cashman et al. (US 20230326135 A1).
Regarding claim 1, Cashman et al. discloses a computer-implemented method for generating a motion for a virtual character (method for virtually representing human body poses includes receiving positioning data detailing parameters of one or more body parts of a human user based at least in part on input from one or more sensors, para. 0005), comprising:
determining a graph representation of a plurality of sets of joints corresponding to a sequence of poses for the virtual character based (One or more mapping constraints are maintained that relate a model articulated representation to a target articulated representation, para. 0005; concurrently estimating poses both for a model articulated representation (e.g., a representation for which a model is trained to output pose estimates), and a target articulated representation (e.g., an articulated representation to be displayed as a virtual representation of a human user), para. 0016) on (i) one or more input poses for the virtual character (one or more mapping constraints are maintained that relate a model articulated representation to a target articulated representation, para. 0005) and (ii) a set of constraints (one or more mapping constraints, para. 0005, para. 0016, para. 0038, see also figure 4) associated with one or more joints included in the plurality of sets of joints;
generating, via execution of a first neural network, a set of updated node states for the plurality of sets of joints based on the graph representation (a pose optimization machine may in some cases be trained to estimate a pose of a virtual articulated representation based on the raw sensor output. For instance, the pose optimization machine may receive image data from the camera as an input, and may be previously-trained to output a pose based at least in part on the image pixel data, para. 0023); and
generating, based on the set of updated node states, the motion that includes (i) a first set of joint positions for the plurality of sets of joints (model pose and target pose for the model and target articulated representations may in some cases be estimated based at least in part on one or more preceding model poses and preceding target poses estimated on one or more preceding time frames, para. 0048) and (ii) a first set of joint orientations for the plurality of sets of joints (one or more mapping constraints may include a pose continuity constraint, specifying a frame-to-frame change limit for one or more joints of the model articulated representation and one or more joints of the target articulated representation, para. 0048).
Regarding claim 2, Cashman et al. discloses the computer-implemented method of claim 1, further comprising training the first neural network using (i) a first loss that is computed between a subset of the first set of joint positions and a second set of joint positions included in the one or more input poses (previously-trained pose optimization machine is trained with positioning data having ground truth labels for the model articulated representation, paras. 0017, 0063, 0066) and (ii) a second loss that is computed between a subset of the first set of joint orientations and a second set of joint orientations included in the one or more input poses (pose continuity constraint, specifying a frame-to-frame change limit for one or more joints of the model articulated representation and one or more joints of the target articulated representation, para. 0048).
Regarding claim 3, Cashman et al. discloses the computer-implemented method of claim 2, further comprising training the first neural network based on one or more additional losses associated with the set of constraints (the one or more mapping constraints may include a pose continuity constraint, specifying a frame-to-frame change limit for one or more joints of the model articulated representation and one or more joints of the target articulated representation, para. 0048).
Regarding claim 5, Cashman et al. discloses the computer-implemented method of claim 1, wherein determining the graph representation comprises: generating, via execution of a second neural network, a first set of embeddings associated with (i) a set of identities for the plurality of sets of joints (pose optimization machine concurrently estimates poses both for the model and target articulated representations, by finding poses that are consistent with the positioning data and also satisfy the mapping constraints, para. 0037) and (ii) a temporal position of each set of joints included in the plurality of sets of joints within the sequence of poses (the model pose and target pose for the model and target articulated representations may in some cases be estimated based at least in part on one or more preceding model poses and preceding target poses estimated on one or more preceding time frames, para. 0048);
determining, based on the one or more input poses and the set of constraints, (i) a second set of joint positions for the plurality of sets of joints and (ii) a second set of joint orientations for the plurality of sets of joints (a model pose of the model articulated representation and a target pose of the target articulated representation based at least in part on the positioning data and the one or more mapping constraints, para. 0100); and
converting, via execution of a third neural network, the second set of joint positions and the second set of joint orientations into a second set of embeddings for the plurality of sets of joints (the previously-trained pose optimization machine is trained with training positioning data having ground truth labels, para. 0100; the model pose and target pose for the model and target articulated representations may in some cases be estimated based at least in part on one or more preceding model poses and preceding target poses estimated on one or more preceding time frames, para. 0048).
Regarding claim 6, Cashman et al. discloses the computer-implemented method of claim 5, wherein the second set of joint positions and the second set of joint orientations are further determined based on an interpolation associated with the one or more input poses and the set of constraints (a pose continuity constraint, specifying a frame-to-frame change limit for one or more joints, para. 0048 which implicitly supports interpolation/smoothing over time.).
Regarding claim 9, Cashman et al. discloses the computer-implemented method of claim 1, wherein the set of constraints (One or more mapping constraints are maintained that relate a model articulated representation to a target articulated representation, para. 0005) comprises at least one of a position constraint (“positioning data” includes any suitable computer data that specifies, or is useable to estimate, the position, orientation, and/or movement of a body part, para. 0021), an orientation constraint, or a ground contact constraint.
Regarding claim 10, Cashman et al. discloses the computer-implemented method of claim 1, wherein the first neural network comprises a set of cross-layer attention blocks associated with a plurality of resolutions for a skeletal structure of the virtual character.
Claim 11, a non-transitory computer-readable media claim. Is rejected for the same reason as claim 1.
Claim 12, a non-transitory computer-readable media claim. Is rejected for the same reason as claim 2.
Claim 13, a non-transitory computer-readable media claim. Is rejected for the same reason as claim 3.
Claim 15, a non-transitory computer-readable media claim. Is rejected for the same reason as claim 5.
Claim 16, a non-transitory computer-readable media claim. Is rejected for the same reason as claim 6.
Claim 13, a non-transitory computer-readable media claim. Is rejected for the same reason as claim 3.
Claim 19, a non-transitory computer-readable media claim. Is rejected for the same reason as claim 9.
Allowable Subject Matter
Claims 4, 7, 8, 10, 14, 17, 18 and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to THOMAS J LETT whose telephone number is (571)272-7464. The examiner can normally be reached Mon-Fri 9-6 ET.
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/THOMAS J LETT/Primary Examiner, Art Unit 2611
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