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 .
Response to Arguments
Applicant’s arguments with respect to claims 21-40 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.
Furthermore, in response to applicant argument, the system of Balkus is more detailed than the claimed invention by providing GUI displaying index, video, audio and event with event types as outlined in Fig. 7B. Applicant argument in regarding art of Acharya, see the additionally cited paras as outlined under 103 rejections below.
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.
Claims 21-40 are rejected under 35 U.S.C. 103 as being unpatentable over Acharya et al. US 2021/0124741 and Alcantara further in view of Balkus et al. US 2004/0268224.
In regarding to claim 21 Acharya teaches:
21. A method comprising: receiving, by a media processing platform, a first dataset comprising media content recorded by a first recording device;
Acharya 0024, 0026, 0030
receiving, by the media processing platform, a second dataset comprising information obtained from a second recording device;
Acharya 0024, 0026, 0030
synchronizing data of the received first and the second datasets based on corresponding timestamp information associated with the first and the second datasets;
Acharya 0024, 0026, 0030
determining whether an event occurred based on the synchronized data;
Acharya 0024, 0026, 0030
upon determining that an event has occurred, automatically classifying the event via an event classification engine;
Acharya 0086-0087
However, Acharya fails to explicitly teach, but Alcantara teaches:
assigning a priority level to the event based on the automatic classification;
Alcantara, 0058, 0064, 0073
Accordingly, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Alcantara with the system of Acharya in order assigning a priority level to the event based on the automatic classification; as such, user enables to recognized the most important event for further action based on the priority image or video detection.
Furthermore, Acharya and Alcantara fails to explicitly teach, but Balkus teaches:
generating an index corresponding to the event, the index comprising time information associated with the event and the assigned priority level [see assigned priority level under Alcantara as outlined above]; and appending the generated index to the media content via an event data track.
Balkus, 0035-0039, 0041, 0053-0054, Fig. 3 and Fig. 7B
Accordingly, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Balkus with the system of Acharya and Alcantara in order generating an index corresponding to the event, the index comprising time information associated with the event; and appending the generated index to the media content via an event data track; as such, enables specification of the temporal and spatial relationships among the media and playback of the presentation with the specified temporal and spatial relationships..--Abstract.
In regarding to claim 22 Acharya, Alcantara and Balkus teaches:
22. The method of claim 21, furthermore, Acharya teaches wherein the media content is received from the first recording device in substantial real-time as streaming data.
Acharya 0026
In regarding to claim 23 Acharya, Alcantara and Balkus teaches:
23. The method of claim 21, furthermore, Acharya teaches wherein the media content is received from the first recording device as an upload after the first recording device has finished recording.
Acharya 0024, 0026, 0030
In regarding to claim 24 Acharya, Alcantara and Balkus teaches:
24. The method of claim 21, furthermore, Acharya teaches wherein the media content comprises at least one of video data or audio data.
Acharya 0024, 0026, 0030
In regarding to claim 25 Acharya, Alcantara and Balkus teaches:
25. The method of claim 21, furthermore, Acharya teaches wherein the second recording device comprises an external device or a sensor installed within the first recording device.
Acharya 0024, 0026, 0030
In regarding to claim 26 Acharya, Alcantara and Balkus teaches:
26. The method of claim 21, furthermore, Acharya teaches wherein the information obtained from the second recording device comprises sensor data obtained from at least one of a gyroscope, an accelerometer, or a compass.
Acharya, Fig. 3B 310 and 312
In regarding to claim 27 Acharya, Alcantara and Balkus teaches:
27. The method of claim 26, furthermore, Acharya teaches further comprising receiving contextual data generated by a third-party service provider based on additional sensor data associated with the media content.
Acharya, 0036, 0054-0055
In regarding to claim 28 Acharya, Alcantara and Balkus teaches:
28. The method of claim 27, furthermore, Acharya teaches wherein the contextual data comprises vehicle data received from an onboard computer of a vehicle.
Acharya, 0036,
In regarding to claim 29 Acharya, Alcantara and Balkus teaches:
29. The method of claim 28, furthermore, Acharya teaches wherein determining whether the event occurred comprises using at least one trained machine learning model configured to: identify one or more data patterns of the sensor data and the contextual data; correlate the identified one or more data patterns to at least a predefined event included in the media content; generate a corresponding likelihood value; and determine whether the event occurred based on the likelihood value.
Acharya, 0029, 0049, 0056
In regarding to claim 30 Acharya, Alcantara and Balkus teaches:
30. The method of claim 29, furthermore, Acharya teaches wherein the at least one trained machine learning model is further configured to compare the likelihood value to a predetermined threshold likelihood value.
Acharya, 0029, 0049, 0056
In regarding to claim 31 Acharya, Alcantara and Balkus teaches:
31. The method of claim 29, furthermore, Acharya teaches wherein a trained machine learning model of the at least one trained machine learning model is configured to determine a context associated with the media content.
Acharya, 0029, 0049, 0056
In regarding to claim 32 Acharya, Alcantara and Balkus teaches:
32. The method of claim 29, furthermore, Acharya teaches wherein a trained machine learning model of the one or more trained machine learning models is configured to identify the predefined event based on information associated with the media content.
Acharya, 0029, 0049, 0056
In regarding to claim 33 Acharya, Alcantara and Balkus teaches:
33. The method of claim 21, furthermore, Acharya teaches wherein an indication of the generated index is stored in a database table that is mapped to the media content.
Acharya, 0087, 0090
In regarding to claim 34 Acharya, Alcantara and Balkus teaches:
34. The method of claim 33, furthermore, Acharya teaches further comprising storing the indexed media content in the database table.
Acharya, 0087, 0090
Claims 35-39 list all similar elements of claims 20-25. Therefore, the supporting rationale of the rejection to claims 20-25 applies equally as well to claims 35-39.
Claim 40 list all similar elements of claim 20. Therefore, the supporting rationale of the rejection to claim 20 applies equally as well to claim 40.
Conclusion
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 DANIEL T TEKLE whose telephone number is (571)270-1117. The examiner can normally be reached Monday-Friday 8:00-4:30 ET.
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/DANIEL T TEKLE/Primary Examiner, Art Unit 2481
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