DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 24 June 2026 has been entered.
Response to Arguments
Applicant’s arguments, see pages 7-9, filed 11 May 2026, with respect to the rejection(s) of claim(s) 1 and similar claims in substance under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Bhatnagar et al. (US 2025/0005851 A1).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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) 1-3, 6-9, 11, 15-17, 19, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pan et al. (US 2025/0209759 A1) in view of Hinz et al. (US 2023/0342893 A1) and further in view of Bhatnagar et al. (US 2025/0005851 A1).
Regarding claim 1, Pan discloses a computer-implemented method for performing visual dubbing of an audiovisual sequence, the computer-implemented method comprising: identifying, based on an actor frame included in the audiovisual sequence, one or more regions included in the actor frame; (Paragraph 0024, tracking a face of an actor in a frame of a first media content item) identifying, based on a dubber frame included in a visual recording of a dubber performance, one or more regions included in the dubber frame (Paragraph 0024, tracking a face of a dubber in a frame of a second media content item). Pan does not clearly disclose generating a plurality of latent vectors based on at least one identified region included in the actor frame and at least one identified region included in the dubber frame, wherein each of a plurality of encoders generates a different latent vector included in the plurality of latent vectors; and generating an output image based on the plurality of latent vectors. Hinz discloses determining different latent vectors for a source digital image and a target digital image using encoders (Figure 3 and paragraphs 0023 and 0053) and using the latent vectors to generate a combined image (Figure 3 and paragraphs 0054-0056). Hinz’s technique for determining latent vectors using encoders for two images to generate a combined image would have been recognized by one of ordinary skill in the art to be applicable to the frames having face regions of an actor and a dubber of Pan and the results would have been predictable in determining latent vectors for frames having faces of an actor and a dubber to generate a combined image. Therefore, the claimed subject matter would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention. Pan in view of Hinz does not clearly disclose using a plurality of encoders included in a machine learning model each associated with a different region. Bhatnagar discloses using multiple different encoders in a machine learning model to generate images using different regions of faces in images, such as the eyes and mouth (Figure 7 and paragraph 0073). Pan in view of Hinz discloses steps for generating an image using an encoder which differed from the claimed process by the substation of using a plurality of decoders of a machine learning model each associated with a different region. Bhatnagar discloses the substituted step of using multiple different decoders of a machine learning model to generate images using different regions of faces in images. As a result, both functions were known in the art to enable a person of ordinary skill in the art to generate images using encoders. Pan in view of Hinz’s decoders could have been substituted with the multiple different encoders of Bhatnagar and the result would have been predictable, resulting in using multiple different encoders in a machine learning model to determine latent vectors for different regions of faces in frames to generate a combined image. Therefore, the claimed subject matter would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention.
Regarding claim 2, Pan discloses wherein the one or more regions included in the actor frame include an actor right eye region, an actor left eye region, and an actor mouth region, and the one or more regions included in the dubber frame include a dubber mouth region (Paragraph 0039, landmarks on the face that can be determined include eye and mouth landmarks).
Regarding claim 3, Pan discloses wherein the one or more regions included in the actor frame further include an actor rest of frame region that includes one or more portions of the actor frame that are not included in any of the actor right eye region, the actor left eye region, or the actor mouth region (Paragraph 0039, background region not part of the faces).
Regarding claim 6, Hinz discloses concatenating the plurality of latent vectors into a combined latent vector (Paragraph 0055, combined latent vector).
Regarding claim 7, Hinz discloses generating, via a decoder in a machine learning model and based on the combined latent vector, a decoded image including a modified actor mouth; (Paragraph 0021 and figure 2, combined digital image generated by a decoder with swapped mouths) and modifying one or more of lighting, contrast, or smoothing associated with the modified actor mouth (Paragraph 0099, global contrast factor for transferring lighting characteristics).
Regarding claim 8, Pan discloses wherein identifying the one or more regions included in the actor frame further comprises identifying a set of two-dimensional (2D) coordinates within the actor frame associated with facial landmarks included in the actor frame (Paragraph 0039, facial landmarks located at the corners of the eyes, at the corners of the mouth, at the ends of the eyeballs, etc.).
Regarding claim 9, Pan discloses wherein the facial landmarks include one or more of an eye, a nose, a mouth, an eyebrow, or a facial contour (Paragraph 0039, eyes and mouth).
Regarding claim 11, Pan in view of Hinz and further in view of Bhatnagar discloses the plurality of encoders correspond to the at least one identified region included in the actor frame and the at least one identified region included in the dubber frame (Bhatnagar, paragraph 0073, different encoders for eyes and mouths of the faces of the actor and dubber in the frames Pan, paragraph 0024).
Regarding claim 15, similar reasoning as discussed in claim 1 is applied.
Regarding claim 16, similar reasoning as discussed in claim 2 is applied.
Regarding claim 17, similar reasoning as discussed in claim 3 is applied.
Regarding claim 19, similar reasoning as discussed in claim 8 is applied.
Regarding claim 20, similar reasoning as discussed in claim 9 is applied.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Pan et al. (US 2025/0209759 A1) in view of Hinz et al. (US 2023/0342893 A1) in view of Bhatnagar et al. (US 2025/0005851 A1) and further in view of Oktay et al. (US 2025/0173613 A1).
Regarding claim 5, Pan in view of Hinz and further in view of Bhatnagar discloses all limitations as discussed in claim 1. Pan in view of Hinz and further in view of Bhatnagar does not clearly disclose wherein each latent vector included in the plurality of latent vectors has an associated length, and the lengths associated with each of the plurality of latent vectors are equal. Oktay discloses latent vectors can be the same as one another (Paragraph 0056). Oktay’s latent vectors that can be the same as one another would have been recognized by one of ordinary skill in the art to be applicable to the latent vectors determine for faces in frames of Pan in view of Hinz and further in view of Bhatnagar and the results would have been predictable in the determining of latent vectors having the same length for faces in frames. Therefore, the claimed subject matter would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention.
Allowable Subject Matter
Claims 4, 10, 12-14, and 18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Regarding claim 4, the prior art does not clearly disclose the computer-implemented method of claim 3, wherein each of the plurality of latent vectors is generated based on a different one of the actor right eye region, the actor left eye region, the actor rest of frame region, and the dubber mouth region.
Regarding claim 10, the prior art does not clearly disclose the computer-implemented method of claim 1, wherein the plurality of latent vectors is a first plurality of latent vectors, further comprising: identifying, based on the output image, one or more regions included in the output image; generating a second plurality of latent vectors based on at least one identified region included in the actor frame and at least one of the one or more regions included in the output image; and generating a double-swapped output image based on the second plurality of latent vectors.
Regarding claim 12, the prior art does not clearly disclose the computer-implemented method of claim 1, wherein generating the plurality of latent vectors further comprises: generating an original dubber mouth latent vector based on an identified original dubber mouth region associated with the dubber frame included in the visual recording of the dubber performance; generating a modified dubber frame based on the identified original dubber mouth region and an identified original actor mouth region associated with the actor frame included in the audiovisual sequence; generating a modified dubber mouth latent vector based on the modified dubber frame; and calculating a latent vector difference based on the original dubber mouth latent vector and the modified dubber mouth latent vector.
Regarding claim 18, similar reasoning as discussed in claim 4 is applied.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Zhang et al. (US 2024/0303908 A1) discloses encoding different regions in space into latent vectors.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHI HOANG whose telephone number is (571)270-3417. The examiner can normally be reached Mon-Fri 8:00-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, JASON CHAN can be reached at (571)272-3022. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PHI HOANG/Primary Examiner, Art Unit 2619
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