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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 01/08/2026 has been entered.
Response to Arguments
Applicant's arguments filed on 01/08/2026 have been fully considered but they are not persuasive.
Regarding the newly amended language, Applicant argues: “Neither AAP A nor Vijayanarasimhan disclose or suggest at least the above highlighted limitations. For example, AAPA merely extracts scenes, it does not further refine boundaries. In addition, Vijayanarasimhan processes the entire video, rather than using clips. Therefore, Applicant requests that the rejection of claim 1, and the claims that depend from claim 1, be withdrawn. The other independent claims contain similar limitations, and they, along with the claims that depend from them, should be allowable for at least similar reasons.”
Examiner notes that the claim indicates that “detecting includes refining” thus it is not clear how the two processes are distinguished. AAPA and Vijayanarasimhan also detect video clips by refining its boundaries to the video segments containing actions of interest. See updated reasons for rejection below.
Examiner also notes that the claims use vague terminology that can read on multiple embodiments found in the prior art. Applicant may wish to clarify the specific computer operations and specific data structures used by the claimed invention.
Claim Construction
Note that, for purposes of compact prosecution, multiple reasons for rejection may be provided for a claim or a part of the claim. The rejection reasons are cumulative, and Applicant should review all the stated reasons as guides to improving the claim language and advancing the prosecution toward an allowance.
Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed by a method claim, or by claim language that does not limit an apparatus claim to a particular structure. However, examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are: (A) “adapted to” or “adapted for” clauses; (B) “wherein” clauses; and (C) “whereby” clauses. M.P.E.P. 2111.04. Other examples are where the claim passively indicates that a function is performed or a structure is used without requiring that the function or structure is a limitation on the claim itself. The clause may be given some weight to the extent it provides "meaning and purpose” to the claimed invention but not when “it simply expresses the intended result” of the invention. In Hoffer v. Microsoft Corp., 405 F.3d 1326, 1329, 74 USPQ2d 1481, 1483 (Fed. Cir. 2005). Further, during prosecution, claim language that may or may not be limiting should be considered non-limiting under the standard of the broadest reasonable interpretation. See M.P.E.P. 904.01(a); In re Morris, 127 F.3d 1048, 44 USPQ2d 1023 (Fed. Cir. 1997).
While Applicant is allowed to be his own lexicographer in describing claim structures, Examiner must reject the claim based on the broadest reasonable interpretation of the claimed elements and not based on the presence of Applicant’s exact phrasing. See In re Morris, 127 F.3d 1048, 44 USPQ2d 1023 (Fed. Cir. 1997); MPEP 904.01(a).
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.
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 paragraph describes the treatment of admitted prior art. In describing an invention, Applicant must inevitably reference that which is known in the art as the basis for the invention, however it is important that the claims particularly point out and distinctly claim that which Applicant regards to be his own invention. See 35 U.S.C. 112 (b) or 35 U.S.C. 112 (pre-AIA ), second paragraph. A statement by an applicant in the specification or made during prosecution identifying prior art is an admission which can be relied upon for both anticipation and obviousness determinations, regardless of whether the admitted prior art would otherwise qualify as prior art under the statutory categories of 35 U.S.C. 102. Riverwood Int ’l Corp. v. R.A. Jones & Co., 324 F.3d 1346, 1354, 66 USPQ2d 1331, 1337 (Fed. Cir. 2003); Constant v. Advanced Micro-Devices Inc., 848 F.2d 1560, 1570, 7 USPQ2d 1057, 1063 (Fed. Cir. 1988). The examiner must determine whether the subject matter identified as prior art is applicant’s own work, or the work of another. In the absence of another credible explanation, examiners should treat such subject matter as the work of another. MPEP 2129.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1, 18-36 are rejected under 35 U.S.C. 103 as being unpatentable over Applicant admitted prior art cited in the Specification, in view of US 20220351516 to Vijayanarasimhan (“Vijayanarasimhan”).
AAPA includes JP 2008022103 to Toshihito (AAPA, Toshihito), cited in Specification Paragraph 3 and provided in an IDS.
Regarding Claim 1: “An information processing device comprising:
acquire a video material (For example, acquiring “a program from moving images recorded on TV programs.” AAPA, Toshihito, Claim 1 and Paragraph 9.)
obtain event information identifying one or more candidate timings of one or more events in the video material, wherein the event information is derived from an analysis of the video material; (“detects important scenes [event information] by dividing the input moving image [analysis of video material] into segments at regular time intervals [candidate scene timings].” AAPA, Toshihito, Claim 1 and Paragraph 9.)
determine one or more inference target segments in the video material based on the event information; (“detects important scenes [event information] by dividing the input moving image into segments at regular time intervals [one or more inference target segments].” AAPA, Toshihito, Claim 1 and Paragraph 9.)
generate inference target data by clipping the one or more inference target segments from the video material as one or more inference windows; and (“detects important scenes [event information] by dividing [clipping] the input moving image into segments at regular time intervals [one or more inference target segments].” AAPA, Toshihito, Claim 1 and Paragraph 9.)
detect one or more event segments within the generated inference target data, by using a trained model configured to detect the one or more event segments within the inference target data, (For example, “detects important scenes by dividing the input moving image into segments at regular time intervals, extracting feature vectors from each segment, and comparing the similarity of feature vectors with reference to the training data.” AAPA, Toshihito, Claim 1 and Paragraph 9. This results in detecting segments with learned features / events.)
wherein the detecting includes refining a boundary of each of the one or more event segments.” (Under the broadest reasonable interpretation consistent with the specification and ordinary skill in the art, a boundary can be a timing boundary, such as a timing boundary between the detected segments and the undetected segments. See Specification, Paragraph 52. Prior art refines the one or more scenes into the detected scenes with boundaries defined by the detected time segments, and the undetected scenes with boundaries defined by the detected time segments. See AAPA, Toshihito, Claim 1 and Paragraph 9.
AAPA does not explicitly teach “a memory storing instructions; and one or more processors configured to execute the instructions to: … ” AAPA implies this manner of execution by using “PCs with TV recording functions” that conventionally operate by executing instructions stored in memory. AAPA, Toshihito, Paragraph 2.
Vijayanarasimhan explicitly teaches the above feature in the context of processing video using learning techniques to generate shortened video segments: “The processor may be a special-purpose processor selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a non-transitory computer-readable storage medium …” Vijayanarasimhan, Paragraph 109.
Therefore, before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to supplement the teachings of AAPA to implement the video processing using “a memory storing instructions; and one or more processors configured to execute the instructions,” as taught in Vijayanarasimhan, in order to implement video processing using on a processor. See Vijayanarasimhan, Paragraph 109.
Finally, in reviewing the present application, there does not seem to be objective evidence that the claim limitations are particularly directed to: addressing a particular problem which was recognized but unsolved in the art, producing unexpected results at the level of the ordinary skill in the art, or any other objective indicators of non-obviousness.
Regarding Claim 18: “The information processing device according to claim 1,
wherein the trained model is further configured to output a score representing an event likelihood for each of the one or more event segments, and (A score embodies as “the evaluation value (importance) of the additional information at each time is calculated, and the section where the evaluation value exceeds the threshold value is extracted as the highlight section” AAPA, Toshihito, Paragraph 6.)
the one or more processors select the one or more event segments based on the score.” (“the evaluation value (importance) of the additional information at each time is calculated, and the section where the evaluation value exceeds the threshold value is extracted [selected] as the highlight section” AAPA, Toshihito, Paragraph 6.)
Regarding Claim 19: “The information processing device according to claim 1, wherein the one or more processors detect a plurality of event segments from the generated inference target data to generate a plurality of video clips corresponding to the plurality of event segments.” (See detected scenes comprising video segments in AAPA, Toshihito, Claim 1 and Paragraph 9. Similarly see “video clip that includes the subset of the video segments.” Vijayanarasimhan, Paragraph 5. Also note that multiple “video clips generated from the videos.” Paragraph 27. See statement of motivation in Claim 1.)
Regarding Claim 20: “The information processing device according to claim 19, wherein the one or more processors generate a digest video by connecting the plurality of video clips in a time scenes.” (For example, digest video can be embodied as a “training video image prepared in advance as sample data of important scenes into segments at regular time intervals” as noted in AAPA, Toshihito, Paragraph 9. Also see an embodiment “wherein the subset of the video segments is further based on the one or more of the video segments that include the first person, generating a first video clip that includes the subset of the video segments, and providing the first video clip to the user as a personalized video clip” Vijayanarasimhan, Paragraph 5. See statement of motivation in Claim 1.)
Regarding Claim 21: “The information processing device according to claim 1,
wherein the one or more processors are further configured to cause a display to present the detected one or more event segments to a user “and providing the first video clip to the user as a personalized video clip” Vijayanarasimhan, Paragraph 5. See statement of motivation in Claim 1.)
for selection or adjustment of the boundary.” (For example, “The important scene selection unit 1 2 reproduces the input moving image, displays the important scene, and receives the user input, and selects an undetected scene that is not detected by the moving image analysis unit 11.” AAPA, Toshihito, Paragraph 16. See similar embodiments in Vijayanarasimhan, Paragraphs 68, 74. See statement of motivation in Claim 1.)
Regarding Claim 22: “The information processing device according to claim 1, wherein the event information includes at least one of a candidate start time, a candidate end time, or a candidate center time derived from the analysis of the video material.” (“As shown in FIG. 6, the important scene information stored here can include additional information such as attributes and likelihoods of each section in addition to the start time and end time of the important scene section.” AAPA, Toshihito, Paragraph 25. See similarly in Vijayanarasimhan, Paragraph 102.)
Regarding Claim 23: “The information processing device according to claim 1, wherein the analysis of the video material includes detecting a change in at least one of audio volume, audio content, or visual motion in the video material to identify the one or more candidate timings.” (For example, “action may be identified based on application of the audio classifier, RGB classifier, and/or the motion classifier … identify video [time] segments from the video that include frames between the start time and the end time for each action in the video.” Vijayanarasimhan, Paragraphs 21-22. See similarly in AAPA, Toshihito, Claim 6. See statement of motivation in Claim 1.)
Regarding Claim 2: “The information processing device according to claim 1, wherein the determine the one or more inference target segments includes determining a range that includes the candidate timing and a predetermined context interval before and/or after the candidate timing.” (“The audio classifier and the RGB classifier may determine an understanding of the scene context and the motion classifier may determine motion ( or motion patterns) within the video, thereby localizing the action within particular frames. … and the results may be combined,” thus including the action frames and the context frames. Vijayanarasimhan, Paragraphs 58, 62,101. See statement of motivation in Claim 1.)
Regarding Claim 25: “The information processing device according to claim 1, wherein the trained model is a neural network trained to input the inference target data and output time information indicating a start point and an end point of the event segment.” (AAPA implies a neural network “probabilistic model, … training data given in advance sufficiently covers the pattern of the highlight scene to be extracted” based on start and end times in the whole video, as in Toshihito, Paragraph 4. Vijayanarasimhan, explicitly teaches using a neural network in Paragraphs 48. See statement of motivation in Claim 1.)
Claim 26, “An information processing method performed by one or more processors” is rejected for reasons stated for Claim 1, because the processing device of Claim 1 implement the method steps of Claim 26.
Claim 27 is rejected for reasons stated for Claim 18 in view of the Claim 26 rejection.
Claim 28 is rejected for reasons stated for Claim 19 in view of the Claim 26 rejection.
Claim 29 is rejected for reasons stated for Claim 20 in view of the Claim 26 rejection.
Claim 30 is rejected for reasons stated for Claim 21 in view of the Claim 26 rejection.
Claim 31, “A non-transitory computer-readable recording medium storing a program causing a computer to execute an information processing method” is rejected for reasons stated for Claim 1, and because prior art teaches: “The processor may be a special-purpose processor selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a non-transitory computer-readable storage medium,” Vijayanarasimhan, Paragraphs 48. See statement of motivation in Claim 1.)
Claim 32 is rejected for reasons stated for Claim 18 in view of the Claim 31 rejection.
Claim 33 is rejected for reasons stated for Claim 19 in view of the Claim 31 rejection.
Claim 34 is rejected for reasons stated for Claim 20 in view of the Claim 31 rejection.
Claim 35 is rejected for reasons stated for Claim 21 in view of the Claim 31 rejection.
Claim 36 is rejected for reasons stated for Claim 24 in view of the Claim 31 rejection.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MIKHAIL ITSKOVICH whose telephone number is (571)270-7940. The examiner can normally be reached Mon. - Thu. 9am - 8pm.
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/MIKHAIL ITSKOVICH/Primary Examiner, Art Unit 2483