Prosecution Insights
Last updated: April 19, 2026
Application No. 18/481,882

GENERATING VIDEO INSIGHTS BASED ON MACHINE-GENERATED TEXT REPRESENTATIONS OF VIDEOS

Non-Final OA §102§103
Filed
Oct 05, 2023
Examiner
MARANDI, JAMES R
Art Unit
2421
Tech Center
2400 — Computer Networks
Assignee
Adobe Inc.
OA Round
1 (Non-Final)
60%
Grant Probability
Moderate
1-2
OA Rounds
2y 10m
To Grant
88%
With Interview

Examiner Intelligence

Grants 60% of resolved cases
60%
Career Allow Rate
292 granted / 491 resolved
+1.5% vs TC avg
Strong +28% interview lift
Without
With
+28.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
11 currently pending
Career history
502
Total Applications
across all art units

Statute-Specific Performance

§101
8.0%
-32.0% vs TC avg
§103
45.4%
+5.4% vs TC avg
§102
24.5%
-15.5% vs TC avg
§112
13.1%
-26.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 491 resolved cases

Office Action

§102 §103
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 . DETAILED ACTION This action is in response to the submission of 9/24/2025 responding to the Restriction Requirement of 7/24/2025. Applicant has elected claims 1-10, and withdrawn claims 11-20. 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 1-4 and 7-9 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Rivera-Rodriguez, USPN 12,063,123 (hereinafter “Rivera-Rodriguez”). Regarding claim 1, Rivera-Rodriguez discloses a computing system (Figs. 1, 2, 8, 9, and 11; Col. 2, lines 35-52; Col. 4, line 35 through Col.8, line 18; Col. 14, line 6 through Col. 17, line 19; Col.18, lines 47 through Col. 22, line34), comprising: a processor (Fig. 11, 1110; Col. 19, lines20-40); and computer storage memory having computer-executable instructions stored thereon which, when executed by the processor (Col. 19, lines 40-52), configure the computing system to perform operations comprising: obtain text data associated with a video (As shown in Fig. 2, there are video streams and content being shared amongst the viewers/ participants. Col. 4, lines 35-45; Col. 5, line 1 through Col. 7, line 47); generate a model prompt to be input into a large language model, the model prompt including the text data associated with the video (Col. 5, line 1 through Col. 7, line 47); obtain, as output from the large language model, a text representation that represents the video in natural language based on the text data (Col. 5, line 1 through Col. 7, line 47); and provide the text representation as input into a machine learning model to generate a video insight that indicates context of the video (Col. 2, lines 35-52; Col. 6, lines 30-32; Col. 8, lines 3-18). Regarding claim 2, Rivera-Rodrigues discloses wherein the text data corresponds with a plurality of modalities of the video, the plurality of modalities including at least audio and images (Col. 5, line 1 through Col. 6, line 67). Regarding claim 3, Rivera-Rodriguez discloses wherein the text data comprises video metadata (Col. 6, lines 33-49), a video description (Col. 6, lines 33-67), a video caption (Col. 6, lines 33-67), a video object (Col. 9, lines 25-30; Col. 11, lines 43-62), and a video transcription (Col. 6, lines 33-67). Further see Fig. 8 and corresponding descriptions. Regarding claim 4, River-Rodriguez further discloses wherein the video description, the video caption, and the video object are identified in association with keyframes extracted from the video (Col. 9, lines 25-30; Col. 11, lines 43-62; Col. 14, lines 6-27). Regarding claim 7, Rivera-Rodriguez discloses wherein the machine learning model that generates the video insight comprises a classifier (Col. 14, line 54 through Col. 15, line14) to identify an emotion class (Fig. 8, 814), a persuasion strategy class, or a topic class (Col. 23, line 64 through Col. 24, line 3). Regarding claim 8, Rivera-Rodriguez discloses wherein the machine learning model that generates the video insight comprises a generator to generate an action or a reason associated with the video (Col. 5, line 61 through Col. 6, line 33). Claim 9 recites similar recitations as claims 7 and 8, therefore, are rejected the same. 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. Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Rivera-Rodriguez, in view of Zhao et al., “Text from Corners: A Novel Approach to Detect Text and Captions in Videos”, IEEE Transactions on Image Processing, Vol. 2, No. 3, March 2011 (hereinafter “Zhao”). Regarding claim 5, Rivera-Rodriguez is not explicit in wherein the video caption and the video object are identified using an optical flow-based approach or a sampling-based approach. However, Zhao discloses a method wherein the video caption and the video object are identified using an optical flow-based approach (Abstract, Page 791, 1st Col., 4th paragraph) or a sampling-based approach Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the system of Rivera-Rodriguez with Zhao’s teachings in order to provide a robust and flexible text detection system (See Zhao’s Abstract for motivation). Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Rivera-Rodriguez, in view of Hawes et al., USPGPUB 2024/0403290 (hereinafter “Hawes”) Regarding claim 6, Rivera-Rodrigues is not explicit in wherein the model prompt is generated by concatenating different types of text data. However, Hawes discloses a method, system, and computer program product for Large Language Model (LLM) optimization (Abstract) wherein the model prompt is generated by concatenating different types of text data (¶ [61]). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the system of Rivera-Rodriguez with Hawes’ teachings in order to optimize and expedite system response times. Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Rivera-Rodriguez, in view of Xu et al., USPGPUB 2022/0237228 (hereinafter “Xu”). Regarding claim 10, Rivera-Rodriguez discloses providing video insight (as analyzed for claim 1) and analysis of the video (Col. 5, line 1 through Col. 6, line 67), and generating tags for the video (Col. 13, lines 3-8). Rivera-Rodriguez is not explicit in providing the video insight for display in association with the video, for analysis of the video, or for a tag of the video. However, Xu discloses a method, system, and computer program product for displaying content (video) to a viewer (Figs. 3 and 8 and corresponding descriptions) and providing the video insight for display in association with the video, for analysis of the video, or for a tag of the video (¶¶ [60], [123]). Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the system of Rivera-Rodriguez with Xu’s teachings in order to provide additional data/ information to a viewer/ user at the same time as the content for further enjoyment and understanding. Contacts Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES R MARANDI whose telephone number is (571)270-1843. The examiner can normally be reached Monday-Friday 8-7 ET flex. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nathan J Flynn can be reached at 571-272-1915. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JAMES R MARANDI/Primary Examiner, Art Unit 2421
Read full office action

Prosecution Timeline

Oct 05, 2023
Application Filed
Dec 26, 2025
Non-Final Rejection — §102, §103
Mar 31, 2026
Interview Requested
Apr 09, 2026
Examiner Interview Summary
Apr 09, 2026
Applicant Interview (Telephonic)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12593101
METHODS AND APPARATUS TO IDENTIFY MEDIA PRESENTATIONS BY ANALYZING NETWORK TRAFFIC
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Patent 12593089
HLS GLOBAL SYNCHRONIZATION AND MULTI-VIEWER WATCH PARTIES
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Patent 12593110
NEWS FEED FOR MEDIA CONTENT SELECTION
2y 5m to grant Granted Mar 31, 2026
Patent 12586373
PROCESSING CONTENT BASED ON NATURAL LANGUAGE QUERIES
2y 5m to grant Granted Mar 24, 2026
Patent 12574572
METHOD AND APPARATUS FOR GENERATING VIDEO STREAM
2y 5m to grant Granted Mar 10, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
60%
Grant Probability
88%
With Interview (+28.2%)
2y 10m
Median Time to Grant
Low
PTA Risk
Based on 491 resolved cases by this examiner. Grant probability derived from career allow rate.

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