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 .
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.
Applicant has amended the title of the invention to overcome the objection to the specification provided in the previous office action.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 07/23/2025 and 01/22/2026 have been considered by the examiner. The submissions are in compliance with the provisions of 37 CFR 1.97.
Response to Arguments
Applicant's arguments filed on 10/22/2025 with respect to claims 1 - 10, 15, and 17 - 25 have been considered but are not persuasive.
Please refer to the following office action, which clearly sets forth the reasons for non-persuasiveness.
Applicant argues that Tremblay fails to teach obtaining, by the client computing device, a target image to be identified based on a photographed picture on a photographing page in response to determining that an image definition of the target image conforms with a predetermined definition condition; the server computing device identifying a target object from the target image; and automatically applying the target effect resource to the target object during a video shooting process by the client computing device; and generating a video based on the target object to which the target effect resource is automatically applied during the video shooting process.
Examiner notes Perfilev clearly teaches obtaining, by the client computing device, a target image to be identified based on a photographed picture on a photographing page in response to determining that an image definition of the target image conforms with a predetermined definition condition (in at least column 6 lines 61 – 62, scene scaling for matching the real-world coordinate space with AR 3D objects; and column 9 lines 40 – 41, Methods for matching the AR-hosting client device coordinates with the server data. Thereby capturing and outputting image as in figure 6); the server computing device identifying a target object from the target image (in at least column 6 lines 61 – 62, scene scaling for matching the real-world coordinate space with AR 3D objects; and column 9 lines 40 – 41, Methods for matching the AR-hosting client device coordinates with the server data. Thereby capturing and outputting image as in figure 6); and automatically applying the target effect resource to the target object during a video shooting process by the client computing device (figure 2 item 209 and figure 3 item 311); and generating a video based on the target object to which the target effect resource is automatically applied during the video shooting process is taught (figure 2 item 211 and figure 3 item 313 and figure 6 final image i.e. augmented reality-image overlaying).
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1 - 10, 15, and 17 - 25 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. Newly added limitations in claims 1 – 10, 15, and 17 - 25 are not disclosed in the original submission dated 03/12/2024, examiner notes that there is no discussion of "predetermined definition condition" in the specification as filed hence "predetermined definition condition" as a whole presents new matter issues. If applicant believes that the limitation was disclosed in the original submission dated 03/12/2024 applicant is asked to kindly specifically point to the specific sections in the original submission and discuss the newly added limitations.
Claim Rejections - 35 USC § 102
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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(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 – 10, 15, and 17 – 25 are rejected under 35 U.S.C. 102(a)(1) [as best understood in view of the 35 U.S.C. 112 rejection above] as being anticipated by Perfilev (US Patent No. 10/497,180).
Regarding claim 1, Perfilev teaches a method of generating videos (abstract), wherein the method is applied to a client computing device (figure 1) and comprises: obtaining , by the client computing device, a target image to be identified based on a photographed picture on a photographing page in response to determining that an image definition of the target image conforms with a predetermined definition condition (in at least column 6 lines 61 – 62, scene scaling for matching the real-world coordinate space with AR 3D objects; and column 9 lines 40 – 41, Methods for matching the AR-hosting client device coordinates with the server data. Thereby capturing and outputting image as in figure 6; figure 6 image from camera; figure 1 item 130 including 101 and 107); transmitting the target image to a server computing device (figure 1 item 102 sending to 103) for the server computing device identifying a target object from the target image (in at least column 6 lines 61 – 62, scene scaling for matching the real-world coordinate space with AR 3D objects; and column 9 lines 40 – 41, Methods for matching the AR-hosting client device coordinates with the server data. Thereby capturing and outputting image as in figure 6); receiving a target effect resource from the server computing device, wherein the target effect resource is determined based on identifying the target object from the target image (figure 1 item 105 sending to item 106 and processing via item 108); automatically applying the target effect resource to the target object during a video shooting process by the client computing device (figure 2 item 209 and figure 3 item 311); and generating a video based on the target object to which the target effect resource is automatically applied during the video shooting process is taught (figure 2 item 211 and figure 3 item 313 and figure 6 final image i.e. augmented reality-image overlaying).
Regarding claim 2, as mentioned above in the discussion of claim 1, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches wherein the obtaining a target image to be identified based on a photographed picture further comprises: obtaining a current image corresponding to the photographed picture as an image with a definition to be determined (figure 1 item 101 camera position); determining whether the definition of the image conforms with a the predetermined definition condition (figure 6 matching orientation and coordinates of image from camera); and determining the image as the target image in response to determining that the definition of the image conforms with the predetermined definition condition (figure 6 overlaying image depending on image from camera along with orientation and coordinates).
Regarding claim 3, as mentioned above in the discussion of claim 2, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches in response to determining that the definition of the image fails to conform with the preset definition condition, obtaining another image from photographed pictures on the photographing page based on a preset rule of extracting frame and replacing the image with the other image (figure 1 item 108); and continuing to execute an operation of determining whether a definition of the other image conforms with the preset definition condition until it is determined that a preset termination condition is met (figure 1 item 109 also figure 6 overlaying the client's camera feed).
Regarding claim 4, as mentioned above in the discussion of claim 2, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches wherein the determining whether the definition of the image conforms with a preset definition condition further comprises: processing the image by a model preconfigured to filter fuzzy images and obtaining an image definition value of the image (column 2 lines 16 – 42; match coordinates along with device orientation; wherein fuzzy images are location not matching the detected coordinates along with device orientation; or figure 2 item 207); determining that the definition of the image conforms with the preset definition condition in response to determining that the image definition value of the image is greater than or equal to a value threshold corresponding to the preset definition condition (column 2 lines 16 – 42; match coordinates along with device orientation i.e. threshold; or figure 2 item 207 shading not needed); and determining that the definition of the image fails to conform with the preset definition condition in response to determining that the image definition value of the image is less than the value threshold corresponding to the preset definition condition (column 2 lines 16 – 42; no match in coordinates along with device orientation i.e. threshold; or figure 2 item 207 shading needed).
Regarding claim 5, as mentioned above in the discussion of claim 3, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches wherein the obtaining another image from photographed pictures on the photographing page based on a preset rule of extracting frame further comprises: extracting one frame of image from images corresponding to the photographed pictures at intervals of every predetermined time period (figure 2 item 211 and figure 3 item 313 and figure 6 final image i.e. augmented reality-image overlaying over time); or extracting one frame of image from images corresponding to the photographed pictures at intervals of every predetermined number of frames (figure 2 item 211 and figure 3 item 313 and figure 6 final image i.e. augmented reality-image overlaying over time).
Regarding claim 6, as mentioned above in the discussion of claim 3, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches in response to determining that a number of frames extracted from the images corresponding to the photographed pictures reaches a preset image extraction number, terminating a process of obtaining another image and determining image definition (column 7 lines 40 – 44; over fixed periods of time, the client device sends its coordinates, as well as rotation angle and projection of the camera to the server); or in response to determining that an image definition value of the image is less than a preset minimum value, terminating the process of obtaining another image and determining image definition (column 7 lines 40 – 44; over fixed periods of time, the client device sends its coordinates, as well as rotation angle and projection of the camera to the server).
Regarding claim 7, as mentioned above in the discussion of claim 1, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches receiving position information indicating a location of the target object in the photographed picture from the server computing device (column 2 lines 16 – 42; match coordinates along with device orientation also figure 6 matching orientation and coordinates of image from camera); and automatically applying the target effect resource to the target object in the photographed picture based on the position information during the video shooting process (figure 6 overlaying image depending on image from camera along with orientation and coordinates).
Regarding claim 8, Perfilev teaches a method of generating videos (abstract), wherein the method is applied to a server computing device (figure 1) and comprises: receiving a target image to be identified from a client computing device, wherein an image definition of the target image conforms with a predetermined definition condition (in at least column 6 lines 61 – 62, scene scaling for matching the real-world coordinate space with AR 3D objects; and column 9 lines 40 – 41, Methods for matching the AR-hosting client device coordinates with the server data. Thereby capturing and outputting image as in figure 6; figure 6 image from camera; figure 1 item 130 including 101 and 107); determining whether the target image contains any one preset object (column 1 line 36 – column 2 line 6; also figure 6 matching orientation and coordinates of image from camera); determining the any one preset object as a target object in response to determining that the target image contains the any one preset object (figure 6 matching orientation and coordinates of image from camera of table); determining a target effect resource corresponding to the target object (figures 5 – 6; figure 6 matching orientation and coordinates of image from camera); and transmitting the target effect resource to the client computing device for generating a video by automatically applying the target effect resource to the target object during a video shooting process of the client computing device (figure 2 item 211 and figure 3 item 313 and figure 6 final image i.e. augmented reality-image overlaying; figure 6 overlaying image depending on image from camera along with orientation and coordinates).
Regarding claim 9, as mentioned above in the discussion of claim 8, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches extracting image features of the target image (figure 6; image from camera used to position the overlay); comparing the image features with feature information corresponding to preset objects (figure 6 matching orientation and coordinates of image from camera); and in response to determining that the image features of the target image match feature information corresponding to the any one preset object, determining the any one preset object as the target object (figure 6 overlaying image depending on image from camera along with orientation and coordinates).
Regarding claim 10, as mentioned above in the discussion of claim 8, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches transmitting position information indicating a location of the target object in the photographed picture to the client computing device such that the client computing device automatically applies the target effect resource to the target object in the photographed picture based on the position information during the video shooting process (figure 6 also figure 3 items 305 - 313).
Regarding claim 15, Perfilev teaches a client computing device (figure 1 and 8) comprising: a memory (figure 8 items 22, 24, and 25), a processor (figure 8 item 21), computer programs stored on the memory and executable by the processor (figure 8 items 36 – 38 also column 10 lines 42 – 50), wherein the computer programs, upon execution by the processor, cause the processor to perform operations comprising: acquiring, by the client computing device, a target image based on a photographed picture from a photographing page in response to determining that an image definition of the target image conforms with a predetermined definition condition (in at least column 6 lines 61 – 62, scene scaling for matching the real-world coordinate space with AR 3D objects; and column 9 lines 40 – 41, Methods for matching the AR-hosting client device coordinates with the server data. Thereby capturing and outputting image as in figure 6; figure 6 image from camera; figure 1 item 130 including 101 and 107); transmitting the target image to a server computing device for the server computing device identifying a target object from the target image (in at least column 6 lines 61 – 62, scene scaling for matching the real-world coordinate space with AR 3D objects; and column 9 lines 40 – 41, Methods for matching the AR-hosting client device coordinates with the server data. Thereby capturing and outputting image as in figure 6, figure 1 item 102 sending to 103); receiving the target effect resource from the server computing device, wherein the target effect resource is determined based on identifying the target object from the target image (figure 1 item 105 sending to item 106 and processing via item 108); automatically applying the target effect resource to the target object during a video shooting process by the client computing device (figure 2 item 209 and figure 3 item 311); and generating a video based on the target object to which the target effect resource is automatically applied during the video shooting process (figure 2 item 211 and figure 3 item 313 and figure 6 final image i.e. augmented reality-image overlaying).
Regarding claim 17, as mentioned above in the discussion of claim 15, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches obtaining a current image corresponding to the photographed picture as an image with a definition to be determined (figure 1 item 101 camera position); determining whether the definition of the image conforms with the predetermined definition condition (figure 6 matching orientation and coordinates of image from camera); and determining the image as the target image in response to determining that the definition of the image conforms with the predetermined definition condition (figure 6 overlaying image depending on image from camera along with orientation and coordinates).
Regarding claim 18, as mentioned above in the discussion of claim 17, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches in response to determining that the definition of the image fails to conform with the preset definition condition, acquiring another image from photographed pictures on the photographing page based on a preset rule of extracting frame and replacing the image with the other image (figure 1 item 108); and continuing to execute an operation of determining whether a definition of the other image conforms with the preset definition condition until it is determined that a preset termination condition is met (figure 1 item 109 also figure 6 overlaying the client's camera feed).
Regarding claim 19, as mentioned above in the discussion of claim 17, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches processing the image by a model preconfigured to filter fuzzy images and obtaining an image definition value of the image (column 2 lines 16 – 42; match coordinates along with device orientation; wherein fuzzy images are location not matching the detected coordinates along with device orientation; or figure 2 item 207); determining that the definition of the image conforms with the preset definition condition in response to determining that the image definition value of the image is greater than or equal to a value threshold corresponding to the preset definition condition (column 2 lines 16 – 42; match coordinates along with device orientation i.e. threshold; or figure 2 item 207 shading not needed); and determining that the definition of the image fails to conform with the preset definition condition in response to determining that the image definition value of the image is less than the value threshold corresponding to the preset definition condition (column 2 lines 16 – 42; no match in coordinates along with device orientation i.e. threshold; or figure 2 item 207 shading needed).
Regarding claim 20, as mentioned above in the discussion of claim 18, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches wherein the acquiring another image from photographed pictures on the photographing page based on a preset rule of extracting frame further comprises: extracting one frame of image from images corresponding to the photographed pictures at intervals of every predetermined time period (figure 2 item 211 and figure 3 item 313 and figure 6 final image i.e. augmented reality-image overlaying over time); or extracting one frame of image from images corresponding to the photographed pictures at intervals of every predetermined number of frames (figure 2 item 211 and figure 3 item 313 and figure 6 final image i.e. augmented reality-image overlaying over time).
Regarding claim 21, as mentioned above in the discussion of claim 18, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches in response to determining that a number of frames extracted from the images corresponding to the photographed pictures reaches a preset image extraction number, terminating a process of obtaining another image and determining image definition (column 7 lines 40 – 44; over fixed periods of time, the client device sends its coordinates, as well as rotation angle and projection of the camera to the server); or in response to determining that an image definition value of the image is less than a preset minimum value, terminating the process of obtaining another image and determining image definition (column 7 lines 40 – 44; over fixed periods of time, the client device sends its coordinates, as well as rotation angle and projection of the camera to the server).
Regarding claim 22, as mentioned above in the discussion of claim 15, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches receiving position information indicating a location of the target object in the photographed picture from the server computing device (column 2 lines 16 – 42; match coordinates along with device orientation also figure 6 matching orientation and coordinates of image from camera); and automatically applying the target effect resource to the target object in the photographed picture based on the position information during the video shooting process (figure 6 overlaying image depending on image from camera along with orientation and coordinates).
Regarding claim 23, Perfilev teaches a server computing device (figure 1), comprising: at least one memory (figure 8 items 22, 24, and 25), at least one processor (figure 8 item 21), and computer programs stored on the at least one memory and executable by the at least one processor (figure 8 items 36 – 38 also column 10 lines 42 – 50), wherein the computer programs, upon execution by the at least one processor, cause the at least one processor to perform operations comprising: receiving a target image from a client computing device , wherein an image definition of the target image conforms with a predetermined definition condition (in at least column 6 lines 61 – 62, scene scaling for matching the real-world coordinate space with AR 3D objects; and column 9 lines 40 – 41, Methods for matching the AR-hosting client device coordinates with the server data. Thereby capturing and outputting image as in figure 6; figure 6 image from camera; figure 1 item 130 including 101 and 107); determining whether the target image contains any one preset object (column 1 line 36 – column 2 line 6; also figure 6 matching orientation and coordinates of image from camera); determining the any one preset object as a target object in response to determining that the target image contains the any one preset object (figure 6 matching orientation and coordinates of image from camera of table); determining a target effect resource corresponding to the target object (figures 5 – 6; figure 6 matching orientation and coordinates of image from camera); and transmitting the target effect resource to the client computing device for generating a video by automatically applying the target effect resource to the target object during a video shooting process of the client computing device (figure 6 overlaying image depending on image from camera along with orientation and coordinates).
Regarding claim 24, as mentioned above in the discussion of claim 23, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches extracting image features of the target image (figure 6; image from camera used to position the overlay); comparing the image features with feature information corresponding to preset objects (figure 6 matching orientation and coordinates of image from camera); and in response to determining that the image features of the target image match feature information corresponding to the any one preset object, determining the any one preset object as the target object (figure 6 overlaying image depending on image from camera along with orientation and coordinates).
Regarding claim 25, as mentioned above in the discussion of claim 23, Perfilev teaches all of the limitations of the parent claim. Additionally, Perfilev teaches transmitting position information indicating a location of the target object in the photographed picture to the client computing device such that the client computing device automatically applies the target effect resource to the target object in the photographed picture based on the position information during the video shooting process (figure 6 also figure 3 items 305 - 313).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
KANEKO (US PgPub No. 2015/0208001) teaches a camera system image recognition and processing.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office Action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Usman A Khan whose telephone number is (571)270-1131. The examiner can normally be reached on M - Th 5:30 AM - 2 PM, F 5:30 AM - Noon.
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Usman Khan
/USMAN A KHAN/Primary Examiner, Art Unit 2637
01/28/2026