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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 06/23/2025 and 02/09/2026 were filed after the mailing date of the application. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 16-19 are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US. Patent App. Pub. No. 2021/0375042, “Chen 1” hereinafter) in view of Chen et al. (US. Patent App. Pub. No. 2008/0037836, “Chen 2”, hereinafter).
As per claim 1, Chen 1 teaches a method for generating a virtual expression, comprising:
obtaining a face region in an original image to obtain a target face image (¶ [7]);
obtaining a first face coefficient for the target face image (Fig. 5, ¶ [81], obtaining a face-shape expression coefficient), wherein the first face coefficient comprises a template expression coefficient and a pose coefficient (Fig. 5, face pose and template coefficient), wherein the template expression coefficient is used to represent a degree of matching between a facial expression and each of one or more templates (¶ [64]), and the pose coefficient is used to represent a rotation angle of a virtual character in three dimensions (¶ [81], implicitly included in a pose information);
according to the target face coefficient, rendering an expression of the virtual character, to obtain the virtual expression (¶ [91], “…render the three-dimensional model of the virtual face according to the texture information of the target face, to obtain the virtual face image”).
Chen 1 does not expressly teach performing time-domain correction on the template expression coefficient and/or the pose coefficient of the first face coefficient, to obtain a target face coefficient, wherein the target face coefficient is associated with a face coefficient for a previous original image before the original image.
However, Chen 2 teaches a similar method of generating virtual facial expression (see Abstract), wherein the method further includes the above features, performing time-domain correction on the template expression coefficient and/or the pose coefficient of the first face coefficient, to obtain a target face coefficient, wherein the target face coefficient is associated with a face coefficient for a previous original image before the original image (¶ [6], “…track the key point of each facial feature of the face image to estimate the key point position of each facial feature on the current face image according to the key position of each facial feature of the previous face image, and correct the key point positions of the corresponding facial features on the virtual face…”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the method as taught by Chen 2 into the method as taught by Chen 1 as addressed above, the advantage of which is to obtain more accurate key point positions (¶ [7]).
As per claim 2, the combined teachings of Chen 1 and Chen 2 substantially include wherein obtaining the face region in the original image to obtain the target face image comprises: performing face detection on the original image, to obtain one or more face regions in the original image (Chen 1, Fig. 4, step 410); selecting a target face region from the one or more face regions (Chen 1, ¶ [25], selecting partial or whole face); and correcting the target face region to obtain the target face image (Chen 1, ¶ [64], adjusting the baseline face model).
Claim 16, which is similar in scope to claim 1 as addressed above, is thus rejected under the same rationale.
Claim 17, which is similar in scope to claim 1 as addressed above, is thus rejected under the same rationale.
Claim 18, which is similar in scope to claim 1 as addressed above, is thus rejected under the same rationale.
Claim 19, which is similar in scope to claim 2 as addressed above, is thus rejected under the same rationale.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US. Patent App. Pub. No. 2021/0375042, “Chen 1”) in view of Chen et al. (US. Patent App. Pub. No. 2008/0037836, “Chen 2”) further in view of Ji et al. (US. Patent App. Pub. No. 2021/0271862, “Ji”).
As per claim 7, the combined Chen 1-Chen 2 does not expressly teach wherein obtaining the first face coefficient for the target face image comprises:
inputting the target face image into a preset face coefficient recognition network, to obtain the first face coefficient for the target face image output by the preset face coefficient recognition network.
However, Ji teaches a similar method of generating facial expression as shown in Fig. 10 and 14, ¶ [106], wherein the method further comprises the above features, i.e., inputting the target face image into a preset face coefficient recognition network, to obtain the first face coefficient for the target face image output by the preset face coefficient recognition network (¶ [10-11]. See also Fig. 3-4, ¶ [71-72]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the method as taught by Ji to the combined method of Chen 1 and Chen 2 as addressed above, the advantage of which is to improve efficiency and real-time performance of expression recognition and improve user experience (¶ [25]).
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (US. Patent App. Pub. No. 2021/0375042, “Chen 1”) in view of Chen et al. (US. Patent App. Pub. No. 2008/0037836, “Chen 2”) further in view of Lyu et al. (US. Patent App. Pub. No. 2022/0101652, “Lyu”).
As per claim 14, the combined Chen 1-Chen 2 does not explicitly teach
in response to determining that no face region is detected in the original image, continuing to detect a next original image; and according to the target face coefficient for the previous original image, obtaining the virtual expression; or,
in response to determining that no face region is detected in the original image and a duration exceeds a set threshold, obtaining the virtual expression according to a preset expression coefficient.
However, in a very similar method of generating facial expression (see ¶ [81-82]), Lyu teaches this feature, i.e., in response to determining that no face region is detected in the original image, continuing to detect a next original image; and according to the target face coefficient for the previous original image, obtaining the virtual expression (¶ [19-26], “…acquiring a default previous facial expression, where the default previous facial expression is preset before a facial expression of the facial image is recognized”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the method as taught by Lyu into the combined Chen 1-Chen 2 method as addressed above, the advantage of which is to quickly determine the degree of a facial expression of a user (¶ [51]).
Allowable Subject Matter
Claims 3-6, 8-13, 20-21 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.
The following is a statement of reasons for the indication of allowable subject matter:
The prior art taken singly or in combination does not teach or suggest, a method for generating virtual expression, among other things, comprising:
….in response to determining that there are a plurality of face regions, for each of the plurality of face regions, calculating a score for the face region according to region parameter data of the face region, wherein the score is used to represent proximity of the face region to a medial axis of the original image; and
determining a face region with a maximum score as the target face region (claims 3 and 20); or
… wherein correcting the target face region to obtain the target face image comprises:
determining a candidate square region corresponding to the target face region, to obtain vertex coordinate data of the candidate square region;
performing affine transformation on the vertex coordinate data of the candidate square region and vertex coordinate data of a preset square, to obtain an affine transformation coefficient, wherein the vertex coordinate data of the preset square comprises a designated origin;
performing affine transformation on the original image by the affine transformation coefficient, to obtain an affine-transformed image; and
extracting, by using the designated origin as a reference, a square region with a preset side length from the affine-transformed image, and determining an image in the square region as the target face image (claim 5); or
…wherein obtaining the first face coefficient for the target face image comprises:
separately blurring and sharpening the target face image, to obtain one or more blurred images and one or more sharpened images;
separately extracting feature data from the target face image, each of the one or more blurred images, and each of the one or more sharpened images, to obtain an original feature image, a blurred feature image, and a sharpened feature image;
concatenating the original feature image, the blurred feature image, and the sharpened feature image, to obtain an initial feature image;
obtaining an importance coefficient of each of feature images in the initial feature image for presenting an expression of the virtual character, and according to the importance coefficient, adjusting the initial feature image, to obtain a target feature image; and
according to the target feature image, determining the template expression coefficient and the pose coefficient, to obtain the first face coefficient (claims 6 and 8); or
…wherein performing the time- domain correction on the template expression coefficient and/or the pose coefficient of the first face coefficient, to obtain the target face coefficient comprises:
obtaining a first face coefficient and a preset weight coefficient of a previous frame before the original image, wherein a sum of the preset weight coefficient of the previous frame and a preset weight coefficient of the original image is 1; and
calculating a weighted sum of the first face coefficient of the original image and the first face coefficient of the previous frame, to obtain the target face coefficient for the original image (claim 11); or
… wherein after performing the time-domain correction on the template expression coefficient and/or the pose coefficient of the first face coefficient, the method further comprises:
obtaining a preset expression adaptation matrix, wherein the expression adaptation matrix indicates a transformation relationship between two face coefficients containing different numbers of templates; and
calculating a product of a time-domain corrected face coefficient and the preset expression adaptation matrix, to obtain the target face coefficient (claim 12).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Hau H. Nguyen whose telephone number is: 571-272-7787. The examiner can normally be reached on MON-FRI from 8:30-5:30.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Tammy Goddard, can be reached on (571) 272-7773.
The fax number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HAU H NGUYEN/Primary Examiner, Art Unit 2611
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