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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 03/30/2026 has been entered.
Response to Amendment
The Amendment filed 03/30/2026 has been entered. Claims 1, 5-11, 15-21, 25, 26, and 30 remain pending. Claims 2-4, 12-14, 22-24, and 27-29 are cancelled.
Response to Arguments
Applicant's arguments filed 03/30/2026 with respect to Claims 1, 11, 21, and 26 have been fully considered but they are not persuasive.
Regarding Claim 1, Applicant argues that the cited portions of He “fail to disclose the claimed determining an image frame with the highest proportion of faces depicted with corresponding eyes,” particularly arguing that the recitation of He of “the largest sum of the white areas of the two eyes” is “not a ratio of open-eyed faces to total faces across a frame as was recited in claim 4 and now amended into claim 1.”
However, amended Claim 1 does not explicitly recite a proportion of faces depicted with two corresponding eyes to the total number of faces, only reciting “the highest proportion of faces depicted with two corresponding eyes.”
Additionally, Claim 1 recites “determining locations for one or more faces,” “determining a quantity of the one or more faces that have two corresponding eyes,” and “determining an image frame from among the plurality of image frames with the highest proportion of faces depicted with two corresponding eyes.” The use of the limitation “one or more” indicates a case where a location of only one face is determined, and thus determining a quantity of the one face that has two corresponding eyes is necessarily either one or zero (binary). Thus, the step of determining an image frame with the highest proportion of faces, which includes a case where only one face exists, is taught by He. The cited portion of He refers to a case of a single-person image. He, [0049] discloses “When the face image is a single person image, the eyeball areas corresponding to the two eyes of the face in the image can be obtained separately. When the eyeball areas corresponding to both eyes are larger than the first threshold, or when the eyeball area corresponding to any of the two eyes is larger than the first threshold, it is determined that the face is in an eye-opening state.”
That is, Applicant argues that the claim requires “a ratio of open-eyed faces to total faces across a frame,” however He satisfies the claim in the case that only one face exists in the frame, where the ratio would is necessarily 1:1. He, [0044] discloses “In the method in the embodiment of the present application, in a plurality of consecutively captured facial images, the mobile terminal may determine a target image according to the features of the human eyes of the face.” He, [0049], discloses a case where “the face image is a single person image,” and discloses “If both eyes of the human face correspond to whites, the face image with the largest sum of the white areas of the two eyes is used as the target image.” Thus, He teaches determining an image frame (a target image) from among the plurality of image frames (a plurality of consecutively captured facial images) with the highest proportion of faces depicted with two corresponding eyes (single person image with the largest sum of white areas of two eyes).
Applicant’s arguments with respect to Claim 5 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 102
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1, 5, 6, 8, 10, 11, 15, 16, 18, 20, 21, 25, 26, and 30 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by He (CN 107734253 A).
Regarding Claim 1, He discloses “A method comprising:
receiving a plurality of image frames” (He, [0031] discloses “In step 102,multiple frames of face images taken continuously are acquired”);
“determining locations for one or more eyes depicted within the plurality of image frames” (He, [0034] discloses “the mobile terminal can extract facial feature points in the face image, such as facial features” and “for example, identify the position of the human eye according to the facial feature point of the human face”; where position of the human eye is a location for one or more eyes)
“determining a first image frame from among the plurality of image frames based on the locations for the one or more eyes” (He, [0033] discloses “Step 104:Determine a target image according to the features of the human eyes in the face image”; where a target image is a first image frame),
“determining an output image frame by blending at least a subset of the plurality of image frames with the first image frame” (He, [0041] discloses “Step 108: Perform fusion processing on the target image and other images whose matching degree exceeds a preset value.” He, [0042] also discloses “image fusion refers to the process of extracting high-quality information in each channel and synthesizing high-quality images by using image processing and computer technology”; where high-quality images are output image frames; where image fusion is determining an output image frame by blending); and
determining locations for one or more faces depicted within the plurality of image frames, wherein determining the locations for the one or more eyes comprises determining the locations for the one or more eyes based on the locations for the one or more faces” (He, [0032] discloses “After the mobile terminal obtains the continuously captured multiple frames of images, it can perform face recognition on the multiple frames of images and obtain the facial images in the multiple frames of images”; where performing face recognition is determining locations for one or more faces. He, [0034] also discloses “After acquiring a plurality of frames of face images that are continuously captured, the mobile terminal can extract facial feature points in the face image, such as facial features” and “for example, identify the position of the human eye according to the facial feature point of the human face”; where position of the human eye is a location for one or more eyes),
“wherein determining the first image frame comprises:
determining, based on the locations for the one or more faces and the locations of the one or more eyes, corresponding faces for each of the one or more eyes” (He, [0034] also discloses “After acquiring a plurality of frames of face images that are continuously captured, the mobile terminal can extract facial feature points in the face image, such as facial features” and “for example, identify the position of the human eye according to the facial feature point of the human face”);
“determining a quantity of the one or more faces that have two corresponding eyes from among the one or more eyes” (He, [0049] discloses “When the eyeball areas corresponding to both eyes are larger than the first threshold, or when the eyeball area corresponding to any of the two eyes is larger than the first threshold, it is determined that the face is in an eye-opening state”; where determining an eye-opening state when both eyes are larger than a threshold is determining a quantity of faces that have two corresponding eyes); “and
determining an image frame from among the plurality of image frames with the highest proportion of faces depicted with two corresponding eyes” (He, [0049] discloses “If both eyes in the human face correspond to whites, the face image with the largest sum of the white areas of the two eyes is used as the target image”; where determining the face image with the largest sum is determining an image frame with the highest proportion of faces with two corresponding eyes; where the claim includes a case of a single image (“one or more faces” indicates only one face may be present in an image). He teaches a case of an image containing a “single person image” (see He, 0049]). Thus, He teaches determining an image frame with the highest proportion of faces depicted with two corresponding eyes, that proportion being 1:1).
Regarding Claim 5, He teaches “The method of claim 1, wherein the image frame from among the plurality of image frames with the highest proportion of faces depicted with two corresponding eyes is a candidate image frame” (He, [0049] discloses “If both eyes in the human face correspond to whites, the face image with the largest sum of the white areas of the two eyes is used as the target image”; where determining the face image with the largest sum is determining an image frame with the highest proportion of faces with two corresponding eyes), “and wherein determining the first image frame further comprises:
determining at least one face within the candidate image frame that does not have two corresponding eyes” (He, [0069] discloses “if the target image does not exist in the multi-frame face image, each face in the multi-frame face image is identified separately, and an open eye corresponding to each face is obtained. Image. For example, there are a face A, a face B, and a face C in all three frames… In image 1, face A is in an open state, face B is in an open state, and face C is in a closed state”; where face C is at least one face within the candidate image frame – image 1 – that does not have two corresponding eyes);
“determining, from among the plurality of image frames, at least one second image frame where the at least one face has two corresponding eyes” (He, [0069] discloses “in image 2, face A is in an open state, face B is in a closed state, and face C is in Eye-open state”; where image 2 is a second image frame where the face – face C – has two corresponding eyes); “and
combining a portion of the at least one second image frame depicting the at least one face with the candidate image frame to form the first image frame” (He, [0070] the mobile terminal selects a matted image corresponding to face A as Fig. 1, a matted image corresponding to face B is Fig. 3, and a matted image corresponding to face C is Fig. 2. Then the mobile terminal extracts a face A from Fig. 1, a face C from Fig. 2, and a face B from Fig. 3)”. He, [0071] discloses “the terminal may fuse the face part with the background image according to the corresponding position information of each face in the cutout image”; where fusing a face part with background is combining a portion of a second image frame with a candidate image frame).
Regarding Claim 6, He teaches “The method of claim 1, wherein the locations for the one or more eyes are determined in response to determining at least one location for at least one face within the plurality of image frames” (He, [0034] discloses “After obtaining the facial feature points, the mobile terminal can extract the human eye features in the human face”).
Regarding Claim 8, He teaches “The method of claim 1, wherein the blending aligns each image frame of the subset of the plurality of image frames with the first image frame before blending the subset of the plurality of image frames with the first image frame” (He, [0041] discloses “Step 108: Perform fusion processing on the target image and other images whose matching degree exceeds a preset value”; where a target image is a first image frame; where fusion processing is blending; where matching is aligning each image frame).
Regarding Claim 10, He teaches “The method of claim 1, wherein the locations of the one or more eyes are determined to include open eyes and to exclude closed eyes” (He, [0044] discloses “Selecting images based on human eye characteristics can screen out images with closed eyes”).
Regarding Claims 11, 15, 16, 18, and 20, Claims 11, 15, 16, 18, and 20 recite a system with elements corresponding to the steps recited in Claims 1, 5, 6, 8, and 10, respectively. Therefore, the recited elements of this claim are mapped to He in the same manner as the corresponding steps in its corresponding method claim. Additionally, He discloses “A system comprising: a memory storing processor-readable code; and at least one processor coupled to the memory, the at least one processor configured to execute the processor-readable code to cause the at least one processor to perform operations” (He, [0017] discloses “a mobile terminal includes a memory and a processor. The memory stores computer-readable instructions. When the instructions are executed by the processor, the processor causes the processor to execute the steps of the method described above”).
Regarding Claims 21 and 25, Claims 21 and 25 recite an image capture device with elements corresponding to the steps recited in Claims 1 and 5, respectively. Therefore, the recited elements of this claim are mapped to He in the same manner as the corresponding steps in its corresponding method claim. Additionally, He discloses “An image capture device (He, [0123] discloses “The image data captured by the imaging device 610 is first processed by the ISP processor 640.” And “The imaging device 610 may include a camera”; where an imaging device is an image capture device), comprising: an image sensor” (He, [0123] discloses “The imaging device 610 may include a camera having one or more lenses 612 and an image sensor 614); “a memory storing processor-readable code; and at least one processor coupled to the memory and to the image sensor, the at least one processor configured to execute the processor-readable code to cause the at least one processor to perform operations” (He, [0017] discloses “a mobile terminal includes a memory and a processor. The memory stores computer-readable instructions. When the instructions are executed by the processor, the processor causes the processor to execute the steps of the method described above”).
Regarding Claims 26 and 30, Claims 26 and 30 recite a non-transitory computer-readable medium storing a program with instructions corresponding to the steps recited in Claims 1 and 5, respectively. Therefore, the recited elements of this claim are mapped to He in the same manner as the corresponding steps in its corresponding method claim. Additionally, He discloses “A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform operations” (He, [0018] discloses “A computer-readable storage medium having stored thereon a computer program, characterized in that when the computer program is executed by a processor, the steps of the method as described above are implemented”).
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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over He (CN 107734253 A) in view of Cheluvaraju et al. (US 2020/0090340 A1).
Regarding Claim 7, He does not explicitly teach “The method of claim 1, wherein the first image frame is further selected as meeting a sharpness threshold.”
However, in an analogous field of endeavor, Cheluvaraju teaches “The method of claim 1, wherein the first image frame is further selected as meeting a sharpness threshold” (Cheluvaraju, [0034] discloses “In an embodiment, value of sharpness of each of the plurality of images may be compared with a predefined sharpness threshold value for selecting the one or more optimal images”).
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified He to incorporate the teachings of Cheluvaraju by selecting optimal images based on a sharpness threshold. Cheluvaraju is directed to images of objects in “multi-layer sample.” He is directed to combining multiple images of objects based on facial attributes. Cheluvaraju is in the same field of endeavor as optimal images must be selected. Thus, one of ordinary skill in the art would be motivated to combine the He and Cheluvaraju references in order to select the most optimal images: Cheluvaraju, [0034] discloses “In an embodiment, value of sharpness of each of the plurality of images may be compared with a predefined sharpness threshold value for selecting the one or more optimal images.”) Accordingly, the combination of He and Cheluvaraju discloses the invention of Claim 7.
Regarding Claim 17, Claim 17 recites a system with elements corresponding to the steps recited in Claim 7. Therefore, the recited elements of this claim are mapped to the combination of He and Cheluvaraju in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the He and Cheluvaraju references, presented in rejection of Claim 7, apply to this claim. Finally, He discloses “A system comprising: a memory storing processor-readable code; and at least one processor coupled to the memory, the at least one processor configured to execute the processor-readable code to cause the at least one processor to perform operations” (He, [0017] discloses “a mobile terminal includes a memory and a processor. The memory stores computer-readable instructions. When the instructions are executed by the processor, the processor causes the processor to execute the steps of the method described above”).
Claims 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over He (CN 107734253 A), in view of Liang (CN 112085686 B).
Regarding Claim 9, He does not explicitly teach “The method of claim 1, wherein the blending is performed according to a multi-frame noise reduction (MFNR) process, wherein the MFNR process uses the first image frame as an anchor frame.”
However, in an analogous field of endeavor, Liang teaches “The method of claim 1, wherein the blending is performed according to a multi-frame noise reduction (MFNR) process, wherein the MFNR process uses the first image frame as an anchor frame” (Liang, page 6, paragraph 2 discloses “When a clear foreground image is generated according to multiple foreground focusing images, the multi-frame noise reduction algorithm can be used for performing noise reduction synthesis processing to multiple foreground focusing images, and the processed image is used as the clear foreground image”).
It would have been obvious to one of ordinary skill in the art before the effective filing
date of the claimed invention to have modified He to incorporate the teachings of Liang by performing a multi-frame noise reduction algorithm. One of ordinary skill in the art would be motivated to combine the He and Liang references in order improve the overall image: Liang, page 3, paragraph 7 discloses “The finally displayed clear image can give attention to the foreground definition and the background definition at the same time, which effectively improves the image shooting effect.” Accordingly, the combination of He and Liang discloses the invention of Claim 9.
Regarding Claim 19, Claim 19 recites a system with elements corresponding to the steps recited in Claim 9. Therefore, the recited elements of this claim are mapped to the combination of He and Liang in the same manner as the corresponding steps in its corresponding method claim. Additionally, the rationale and motivation to combine the He and Liang references, presented in rejection of Claim 9 apply to this claim. Finally, He discloses “A system comprising: a memory storing processor-readable code; and at least one processor coupled to the memory, the at least one processor configured to execute the processor-readable code to cause the at least one processor to perform operations” (He, [0017] discloses “a mobile terminal includes a memory and a processor. The memory stores computer-readable instructions. When the instructions are executed by the processor, the processor causes the processor to execute the steps of the method described above”).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAROLINE TABANCAY DUFFY whose telephone number is (703)756-1859. The examiner can normally be reached Monday - Friday 8:00 am - 5:30 pm.
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/CAROLINE TABANCAY DUFFY/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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