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 .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/forms/. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Instant Application
Patent No. 12,277,955
(Claim 1)
1. A method, executed by one or more processors, for generation of a video montage from a collection of video clips taken from a plurality of video files, comprising: determining a relevance of a video file of the plurality of video files; generating a video clip by trimming the video file, a length of the video clip being based on the determined relevance of the video file, wherein trimming the video file comprises: trimming the video file to generate a video clip of a first length based on the video file being less relevant, and trimming the video file to generate a video clip of a second length that is greater than the first length based on the video file being more relevant; and adding the video clip to the video montage.
(Claim 2)
2. The method of claim 1, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face.
(Claim 3)
3. The method of claim 1, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face as well as including speech.
(Claim 4)
4. The method of claim 1, further comprising: performing facial recognition to identify a portion of the video file that includes a face of a specific user of a device.
(Claim 5)
5. The method of claim 4, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the specific user of the device.
(Claim 6)
6. The method of claim 1, further comprising: performing facial recognition to identify a portion of the video file that includes a face of a person having a relationship with a specific user of a device.
(Claim 7)
7. The method of claim 6, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the person having the relationship with the specific user of the device.
(Claim 8)
8. The method of claim 1, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a face, as well as a caption.
(Claim 9)
9. The method of claim 1, further comprising: creating a video montage file by adding a plurality of video clips from the collection of video clips together; and adding an audio track to the video montage file.
(Claim 10)
10. A computing apparatus comprising: at least one processor; and a memory storing instructions that, when executed by the at least one processor, configure the computing apparatus to perform operations to generate a video montage from a collection of video clips taken from a plurality of video files, the operations comprising: determining a relevance of a video file of the plurality of video files; generating a video clip by trimming the video file, a length of the video clip being based on the determined relevance of the video file, wherein trimming the video file comprises: trimming the video file to generate a video clip of a first length based on the video file being less relevant, and trimming the video file to generate a video clip of a second length that is greater than the first length based on the video file being more relevant; and adding the video clip to the video montage.
(Claim 11)
11. The computing apparatus of claim 10, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face.
(Claim 12)
12. The computing apparatus of claim 10, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face as well as including speech.
(Claim 13)
13. The computing apparatus of claim 10,wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a face of a user of the computing apparatus.
(Claim 14)
14. The computing apparatus of claim 10, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a face of a person having a relationship with a user of the computing apparatus.
(Claim 15)
15. The computing apparatus of claim 10, wherein the operations further comprise: creating a video montage file by adding a plurality of video clips from the collection of video clips together; and adding an audio track to the video montage file.
(Claim 16)
16. A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to perform operations to generate a video montage from a collection of video clips taken from a plurality of video files, the operations comprising: determining a relevance of a video file of the plurality of video files; generating a video clip by trimming the video file, a length of the video clip being based on the determined relevance of the video file, wherein trimming the video file comprises: trimming the video file to generate a video clip of a first length based on the video file being less relevant, and trimming the video file to generate a video clip of a second length that is greater than the first length based on the video file being more relevant; and adding the video clip to the video montage.
(Claim 17)
17. The computer-readable storage medium of claim 16, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face.
(Claim 18)
18. The computer-readable storage medium of claim 16, wherein trimming the video file to generate a video clip of the second length based on the video file including a close up of a face as well as including speech.
(Claim 19)
19. The computer-readable storage medium of claim 16, further comprising: performing facial recognition to identify a portion of the video file that includes a face of a user of the computer, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the user of the computer.
(Claim 20)
20. The computer-readable storage medium of claim 16, further comprising: performing facial recognition to identify a portion of the video file that includes a face of a person having a relationship with a user of the computer, wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the person having the relationship with the user of the computer.
(Claim 1)
1. A method, executed by one or more processors, for generation of a video montage from a collection of video clips taken from a plurality of video files, comprising: performing facial recognition on a video file of the plurality of video files to identify a portion of the video file including a face; determining a relevance of the face in the portion of the video file; generating a video clip by trimming the portion of the video file including the face, from the video file, a length of the video clip being based on the relevance of the face in the video file; and adding the video clip to the video montage, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to a first length based on the face being less relevant; and trimming the portion of the video file to a second length that is greater than the first length based on the face being more relevant.
(Claim 1 above and Claim 2 below include the claimed limitations of Claim 2 of the Instant Application)
(Claim 2)
2. The method of claim 1, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the face not being a close up of the face; and trimming the portion of the video file to the second length that is greater than the first length based on the face being a close up of the face.
(Claim 1, Claim 2 above and Claim 3 below include the claimed limitations of Claim 3 of the Instant Application)
(Claim 3)
3. The method of claim 1, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the portion of the video file not including speech; and trimming the portion of the video file to the second length that is greater than the first length based on the portion including the face as well as speech.
(Claim 1 above includes the claimed limitations of Claim 4 of the Instant Application)
(Claim 1 above and Claim 4 below include the claimed limitations of Claim 5 of the Instant Application)
(Claim 4)
4. The method of claim 1, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the portion not including a face of a user of a device including at least one of the one or more processors; and trimming the portion of the video file to the second length that is greater than the first length based on the portion of the video file including a face of the user of the device.
(Claim 1 above and Claim 5 below include the claimed limitations of Claim 6 of the Instant Application)
5. The method of claim 1, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the portion not including a face of a person having a relationship with a user of a device including at least one of the one or more processors; and trimming the portion of the video file to the second length that is greater than the first length based on the portion including a face of a person having a relationship with the user of a device.
(Claim 5 above includes the claimed limitations of Claim 7 of the Instant Application)
(Claim 1 above and Claim 6 below include the claimed limitations of Claim 8 of the Instant Application)
(Claim 6)
6. The method of claim 1, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file that includes the face but not a caption to the first length; and trimming the portion of the video file that includes the face, as well as a caption to the second length that is greater than the first length.
(Claim 7 below includes the claimed limitations of Claim 9 of the Instant Application)
7. The method of claim 1, further comprising: creating a video montage file by adding a plurality of video clips from the collection of video clips together; and adding an audio track to the video montage file.
(Claim 8)
8. A computing apparatus comprising: one or more processors; and a memory storing instructions that, when executed by the one or more processors, configure the computing apparatus to perform operations to generate a video montage from a collection of video clips taken from a plurality of video files, the operations comprising: performing facial recognition on a video file of the plurality of video files to identify a portion of the video file including a face; determining a relevance of the face in the portion of the video file; generating a video clip by trimming the portion of the video file including the face, from the video file, a length of the video clip being based on the relevance of the face in the video file; and adding the video clip to the video montage, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to a first length based on the face being less relevant; and trimming the portion of the video file to a second length that is greater than the first length based on the face being more relevant.
(Claim 8 above and Claim 9 below include the claimed limitations of Claim 11 of the Instant Application)
(Claim 9)
9. The computing apparatus of claim 8, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the face not being a close up of the face; and trimming the portion of the video file to a second length that is greater than the first length based on the face being a close up of the face.
(Claim 8 above and Claim 10 below include the claimed limitations of Claim 12 of the Instant Application)
(Claim 10)
10. The computing apparatus of claim 8, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the portion of the video file not including speech; and trimming the portion of the video file to the second length that is greater than the first length based on the portion including the face as well as speech.
(Claim 8 above and Claim 11 below include the claimed limitations of Claim 13 of the Instant Application)
(Claim 11)
11. The computing apparatus of claim 8, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the portion not including a face of a user of the computing apparatus; and trimming the portion of the video file to the second length that is greater than the first length based on the portion of the video file including a face of the user of the computing apparatus.
(Claim 8 above and Claim 12 below include the claimed limitations of Claim 14 of the Instant Application)
(Claim 12)
12. The computing apparatus of claim 8, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the portion not including a face of a person having a relationship with a user of the computing apparatus; and trimming the portion of the video file to the second length that is greater than the first length based on the portion including a face of a person having a relationship with the user of a device.
(Claim 13)
13. The computing apparatus of claim 8, wherein the operations further comprise: creating a video montage file by adding a plurality of video clips from the collection of video clips together; and adding an audio track to the video montage file.
(Claim 14)
14. A non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to perform operations to generate a video montage from a collection of video clips taken from a plurality of video files, the operations comprising: performing facial recognition on a video file of the plurality of video files to identify a portion of the video file including a face; determining a relevance of the face in the portion of the video file; generating a video clip by trimming the portion of the video file including the face, from the video file, a length of the video clip being based on the relevance of the face in the video file; and adding the video clip to the video montage, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to a first length based on the face being less relevant; and trimming the portion of the video file to a second length that is greater than the first length based on the face being more relevant.
(Claim 14 above and Claim 15 below include the claimed limitations of Claim 17 of the Instant Application)
(Claim 15)
15. The computer-readable storage medium of claim 14, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the face not being a close up of the face; and trimming the portion of the video file to the second length that is greater than the first length based on the face being a close up of the face.
(Claim 14 above and Claim 16 below include the claimed limitations of Claim 18 of the Instant Application)
(Claim 16)
16. The computer-readable storage medium of claim 14, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the portion of the video file not including speech; and trimming the portion of the video file to the second length that is greater than the first length based on the portion including the face as well as speech.
(Claim 14 above and Claim 17 below include the claimed limitations of Claim 19 of the Instant Application)
(Claim 17)
17. The computer-readable storage medium of claim 14, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the portion not including a face of a user of the computer; and trimming the portion of the video file to the second length that is greater than the first length based on the portion of the video file including a face of the user the computer.
(Claim 14 above and Claim 18 below include the claimed limitations of Claim 20 of the Instant Application)
(Claim 18)
18. The computer-readable storage medium of claim 14, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file to the first length based on the portion not including a face of a person having a relationship with a user of the computer; and trimming the portion of the video file to a second length that is greater than the first length based on the portion including a face of a person having a relationship with the user of a device.
(Claim 19)
19. The computer-readable storage medium of claim 14, wherein trimming the portion of the video file including a face comprises: trimming the portion of the video file that includes the face but not a caption to the first length; and trimming the portion of the video file that includes the face, as well as a caption to the second length that is greater than the first length.
(Claim 20)
20. The computer-readable storage medium of claim 14, wherein the operations further comprise: creating a video montage file by adding a plurality of video clips from the collection of video clips together; and adding an audio track to the video montage file.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of Patent No. US 12,277,955.
Re claim 1, the conflicting claims are not patentably distinct from each other because claim 1 of the Instant Application is anticipated by claim 1 of the Patent No. 12,277,955.
Re claim 2, the conflicting claims are not patentably distinct from each other because claim 2 of the Instant Application is recited in claims 1 and 2 of the Patent No. 12,277,955.
Re claim 3, the conflicting claims are not patentably distinct from each other because claim 3 of the Instant Application is recited in claims 1, 2 and 3 of the Patent No. 12,277,955.
Re claim 4, the conflicting claims are not patentably distinct from each other because claim 4 of the Instant Application is recited in claim 1 of the Patent No. 12,277,955.
Re claim 5, the conflicting claims are not patentably distinct from each other because claim 5 of the Instant Application is recited in claims 1 and 4 of the Patent No. 12,277,955.
Re claim 6, the conflicting claims are not patentably distinct from each other because claim 6 of the Instant Application is recited in claims 1 and 5 of the Patent No. 12,277,955.
Re claim 7, the conflicting claims are not patentably distinct from each other because claim 7 of the Instant Application is recited in claim 5 of the Patent No. 12,277,955.
Re claim 8, the conflicting claims are not patentably distinct from each other because claim 8 of the Instant Application is recited in claims 1 and 6 of the Patent No. 12,277,955.
Re claim 9, the conflicting claims are not patentably distinct from each other because claim 9 of the Instant Application is recited in claim 7 of the Patent No. 12,277,955.
Re claim 10, the conflicting claims are not patentably distinct from each other because claim 10 of the Instant Application is anticipated by claim 8 of the Patent No. 12,277,955.
Re claim 11, the conflicting claims are not patentably distinct from each other because claim 11 of the Instant Application is recited in claims 8 and 9 of the Patent No. 12,277,955.
Re claim 12, the conflicting claims are not patentably distinct from each other because claim 12 of the Instant Application is recited in claims 8 and 10 of the Patent No. 12,277,955.
Re claim 13, the conflicting claims are not patentably distinct from each other because claim 13 of the Instant Application is recited in claims 8 and 11 of the Patent No. 12,277,955.
Re claim 14, the conflicting claims are not patentably distinct from each other because claim 14 of the Instant Application is recited in claims 8 and 12 of the Patent No. 12,277,955.
Re claim 15, the conflicting claims are not patentably distinct from each other because claim 15 of the Instant Application is recited in claim 13 of the Patent No. 12,277,955.
Re claim 16, the conflicting claims are not patentably distinct from each other because claim 16 of the Instant Application is anticipated by claim 14 of the Patent No. 12,277,955.
Re claim 17, the conflicting claims are not patentably distinct from each other because claim 17 of the Instant Application is recited in claims 14 and 15 of the Patent No. 12,277,955.
Re claim 18, the conflicting claims are not patentably distinct from each other because claim 18 of the Instant Application is recited in claims 14 and 16 of the Patent No. 12,277,955.
Re claim 19, the conflicting claims are not patentably distinct from each other because claim 19 of the Instant Application is recited in claims 14 and 17 of the Patent No. 12,277,955.
Re claim 20, the conflicting claims are not patentably distinct from each other because claim 20 of the Instant Application is recited in claims 14 and 18 of the Patent No. 12,277,955.
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 (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 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, 10 and 16 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Haim et al. (US 2023/0274547 A1)(hereinafter Haim).
Re claim 1, Haim discloses a method, executed by one or more processors, for generation of a video montage from a collection of video clips taken from a plurality of video files, comprising (i.e. a server processor 952 of the server system 998 and automatically trimmed to create trimmed video clip segments 802 using a video trimming algorithm 945 comprising computer executable instructions stored in server memory 954 (FIG. 9) paragraph 66): determining a relevance of a video file of the plurality of video files (see figs. 10-11 ¶s 66, 67, 86 for determining a relevance of a video file of the plurality of video files (i.e. in an example, video highlights (stories) are automatically generated at the end of each day, the system looks at each image taken during the day (or a subset thereof) and selects the best portions (highlights), e.g., based on similarity and time bucketing, this may be performed with a server configured to receive video clips from a mobile device, such as eyewear, the server has an electronic processor enabled to execute computer instructions to process the video clips to identify one or more characteristics in the frames of the video clips as described in paragraph 24, furthermore, each video clip 800 is considered a raw video clip, meaning the video clip 800 is created from when the user enables the cameras 114A-B until the user disables the cameras, in an unedited form, these video clips 800 are automatically uploaded by processor 932 to the server system 998 over network 995 upon creation as described in fig. 8 paragraph 65)); generating a video clip by trimming the video file, a length of the video clip being based on the determined relevance of the video file, wherein trimming the video file (see figs. 10-11 ¶s 66, 86 for generating a video clip by trimming the video file, a length of the video clip being based on the determined relevance of the video file, wherein trimming the video file (i.e. in an example, video highlights (stories) are automatically generated at the end of each day, the system looks at each image taken during the day (or a subset thereof) and selects the best portions (highlights), e.g., based on similarity and time bucketing, this may be performed with a server configured to receive video clips from a mobile device, such as eyewear, the server has an electronic processor enabled to execute computer instructions to process the video clips to identify one or more characteristics in the frames of the video clips as described in paragraph 24, furthermore, based on a set of rules stored in server memory 954 and the gathered per-frame information, the server processor 952 automatically determines trim points and creates the trimmed video clip segments 802, referred to herein as auto editing, the segments of the video clip 800 that do not meet the set of rules are omitted by server processor 952 from the trimmed video clip segments 802 as described in fig. 8 paragraph 67)); comprises: trimming the video file to generate a video clip of a first length based on the video file being less relevant, and trimming the video file to generate a video clip of a second length that is greater than the first length based on the video file being more relevant (see ¶s 24, 66 for trimming the video file to generate a video clip of a first length based on the video file being less relevant, and trimming the video file to generate a video clip of a second length that is greater than the first length based on the video file being more relevant (i.e. based on a set of rules stored in server memory 954 and the gathered per-frame information, the server processor 952 automatically determines trim points and creates the trimmed video clip segments 802, referred to herein as auto editing, the segments of the video clip 800 that do not meet the set of rules are omitted by server processor 952 from the trimmed video clip segments 802 as described in fig. 8 paragraph 67, furthermore, the server processor 952 then creates a summary from the trimmed video clip segments 802 using a video highlights algorithm 950 (FIG. 9), as will be described in more detail with reference to FIG. 10, the summary of the trimmed video clip segments 802 is a set that is less than all the trimmed video clip segments 802 and is a subset of the trimmed video clip segments 802, the summary of trimmed video clip segments 802 is referred to as video highlights 804, the video highlights algorithm 950 determines which of the trimmed video clip segments 802 are suitable to generate the video highlights 804, based on the number of trimmed video clip segments 802, their combined length in time, and other user determined variables as described in fig. 8 paragraph 68); and adding the video clip to the video montage (see ¶s 24, 66, 67 for adding the video clip to the video montage (i.e. the server processor 952 then creates a summary from the trimmed video clip segments 802 using a video highlights algorithm 950 (FIG. 9), as will be described in more detail with reference to FIG. 10, the summary of the trimmed video clip segments 802 is a set that is less than all the trimmed video clip segments 802 and is a subset of the trimmed video clip segments 802, the summary of trimmed video clip segments 802 is referred to as video highlights 804, the video highlights algorithm 950 determines which of the trimmed video clip segments 802 are suitable to generate the video highlights 804, based on the number of trimmed video clip segments 802, their combined length in time, and other user determined variables as described in fig. 8 paragraph 68)
Re claim 10, Haim discloses a computing apparatus comprising: at least one processor (i.e. processor as described in fig. 9 paragraph 66); and a memory storing instructions that, when executed by the at least one processor, configure the computing apparatus to perform operations to generate a video montage from a collection of video clips taken from a plurality of video files, the operations comprising (i.e. a server processor 952 of the server system 998 and automatically trimmed to create trimmed video clip segments 802 using a video trimming algorithm 945 comprising computer executable instructions stored in server memory 954 (FIG. 9) paragraph 66): determining a relevance of a video file of the plurality of video files (see figs. 10-11 ¶s 66, 67, 86 for determining a relevance of a video file of the plurality of video files (i.e. in an example, video highlights (stories) are automatically generated at the end of each day, the system looks at each image taken during the day (or a subset thereof) and selects the best portions (highlights), e.g., based on similarity and time bucketing, this may be performed with a server configured to receive video clips from a mobile device, such as eyewear, the server has an electronic processor enabled to execute computer instructions to process the video clips to identify one or more characteristics in the frames of the video clips as described in paragraph 24, furthermore, each video clip 800 is considered a raw video clip, meaning the video clip 800 is created from when the user enables the cameras 114A-B until the user disables the cameras, in an unedited form, these video clips 800 are automatically uploaded by processor 932 to the server system 998 over network 995 upon creation as described in fig. 8 paragraph 65)); generating a video clip by trimming the video file, a length of the video clip being based on the determined relevance of the video file, wherein trimming the video file (see figs. 10-11 ¶s 66, 86 for generating a video clip by trimming the video file, a length of the video clip being based on the determined relevance of the video file, wherein trimming the video file (i.e. in an example, video highlights (stories) are automatically generated at the end of each day, the system looks at each image taken during the day (or a subset thereof) and selects the best portions (highlights), e.g., based on similarity and time bucketing, this may be performed with a server configured to receive video clips from a mobile device, such as eyewear, the server has an electronic processor enabled to execute computer instructions to process the video clips to identify one or more characteristics in the frames of the video clips as described in paragraph 24, furthermore, based on a set of rules stored in server memory 954 and the gathered per-frame information, the server processor 952 automatically determines trim points and creates the trimmed video clip segments 802, referred to herein as auto editing, the segments of the video clip 800 that do not meet the set of rules are omitted by server processor 952 from the trimmed video clip segments 802 as described in fig. 8 paragraph 67)) comprises: trimming the video file to generate a video clip of a first length based on the video file being less relevant, and trimming the video file to generate a video clip of a second length that is greater than the first length based on the video file being more relevant (see ¶s 24, 66 for trimming the video file to generate a video clip of a first length based on the video file being less relevant, and trimming the video file to generate a video clip of a second length that is greater than the first length based on the video file being more relevant (i.e. based on a set of rules stored in server memory 954 and the gathered per-frame information, the server processor 952 automatically determines trim points and creates the trimmed video clip segments 802, referred to herein as auto editing, the segments of the video clip 800 that do not meet the set of rules are omitted by server processor 952 from the trimmed video clip segments 802 as described in fig. 8 paragraph 67, furthermore, the server processor 952 then creates a summary from the trimmed video clip segments 802 using a video highlights algorithm 950 (FIG. 9), as will be described in more detail with reference to FIG. 10, the summary of the trimmed video clip segments 802 is a set that is less than all the trimmed video clip segments 802 and is a subset of the trimmed video clip segments 802, the summary of trimmed video clip segments 802 is referred to as video highlights 804, the video highlights algorithm 950 determines which of the trimmed video clip segments 802 are suitable to generate the video highlights 804, based on the number of trimmed video clip segments 802, their combined length in time, and other user determined variables as described in fig. 8 paragraph 68); and adding the video clip to the video montage (see ¶s 24, 66, 67 for adding the video clip to the video montage (i.e. the server processor 952 then creates a summary from the trimmed video clip segments 802 using a video highlights algorithm 950 (FIG. 9), as will be described in more detail with reference to FIG. 10, the summary of the trimmed video clip segments 802 is a set that is less than all the trimmed video clip segments 802 and is a subset of the trimmed video clip segments 802, the summary of trimmed video clip segments 802 is referred to as video highlights 804, the video highlights algorithm 950 determines which of the trimmed video clip segments 802 are suitable to generate the video highlights 804, based on the number of trimmed video clip segments 802, their combined length in time, and other user determined variables as described in fig. 8 paragraph 68)
Re claim 16, Haim discloses a non-transitory computer-readable storage medium, the computer-readable storage medium including instructions that when executed by a computer, cause the computer to perform operations to generate a video montage from a collection of video clips taken from a plurality of video files, the operations comprising (i.e. a server processor 952 of the server system 998 and automatically trimmed to create trimmed video clip segments 802 using a video trimming algorithm 945 comprising computer executable instructions stored in server memory 954 (FIG. 9) paragraph 66): determining a relevance of a video file of the plurality of video files (see figs. 10-11 ¶s 66, 67, 86 for determining a relevance of a video file of the plurality of video files (i.e. in an example, video highlights (stories) are automatically generated at the end of each day, the system looks at each image taken during the day (or a subset thereof) and selects the best portions (highlights), e.g., based on similarity and time bucketing, this may be performed with a server configured to receive video clips from a mobile device, such as eyewear, the server has an electronic processor enabled to execute computer instructions to process the video clips to identify one or more characteristics in the frames of the video clips as described in paragraph 24, furthermore, each video clip 800 is considered a raw video clip, meaning the video clip 800 is created from when the user enables the cameras 114A-B until the user disables the cameras, in an unedited form, these video clips 800 are automatically uploaded by processor 932 to the server system 998 over network 995 upon creation as described in fig. 8 paragraph 65)); generating a video clip by trimming the video file, a length of the video clip being based on the determined relevance of the video file, wherein trimming the video file (see figs. 10-11 ¶s 66, 86 for generating a video clip by trimming the video file, a length of the video clip being based on the determined relevance of the video file, wherein trimming the video file (i.e. in an example, video highlights (stories) are automatically generated at the end of each day, the system looks at each image taken during the day (or a subset thereof) and selects the best portions (highlights), e.g., based on similarity and time bucketing, this may be performed with a server configured to receive video clips from a mobile device, such as eyewear, the server has an electronic processor enabled to execute computer instructions to process the video clips to identify one or more characteristics in the frames of the video clips as described in paragraph 24, furthermore, based on a set of rules stored in server memory 954 and the gathered per-frame information, the server processor 952 automatically determines trim points and creates the trimmed video clip segments 802, referred to herein as auto editing, the segments of the video clip 800 that do not meet the set of rules are omitted by server processor 952 from the trimmed video clip segments 802 as described in fig. 8 paragraph 67)) comprises: trimming the video file to generate a video clip of a first length based on the video file being less relevant, and trimming the video file to generate a video clip of a second length that is greater than the first length based on the video file being more relevant (see ¶s 24, 66 for trimming the video file to generate a video clip of a first length based on the video file being less relevant, and trimming the video file to generate a video clip of a second length that is greater than the first length based on the video file being more relevant (i.e. based on a set of rules stored in server memory 954 and the gathered per-frame information, the server processor 952 automatically determines trim points and creates the trimmed video clip segments 802, referred to herein as auto editing, the segments of the video clip 800 that do not meet the set of rules are omitted by server processor 952 from the trimmed video clip segments 802 as described in fig. 8 paragraph 67, furthermore, the server processor 952 then creates a summary from the trimmed video clip segments 802 using a video highlights algorithm 950 (FIG. 9), as will be described in more detail with reference to FIG. 10, the summary of the trimmed video clip segments 802 is a set that is less than all the trimmed video clip segments 802 and is a subset of the trimmed video clip segments 802, the summary of trimmed video clip segments 802 is referred to as video highlights 804, the video highlights algorithm 950 determines which of the trimmed video clip segments 802 are suitable to generate the video highlights 804, based on the number of trimmed video clip segments 802, their combined length in time, and other user determined variables as described in fig. 8 paragraph 68); and adding the video clip to the video montage (see ¶s 24, 66, 67 for adding the video clip to the video montage (i.e. the server processor 952 then creates a summary from the trimmed video clip segments 802 using a video highlights algorithm 950 (FIG. 9), as will be described in more detail with reference to FIG. 10, the summary of the trimmed video clip segments 802 is a set that is less than all the trimmed video clip segments 802 and is a subset of the trimmed video clip segments 802, the summary of trimmed video clip segments 802 is referred to as video highlights 804, the video highlights algorithm 950 determines which of the trimmed video clip segments 802 are suitable to generate the video highlights 804, based on the number of trimmed video clip segments 802, their combined length in time, and other user determined variables as described in fig. 8 paragraph 68)
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.
Claims 2-8, 11-14 and 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Haim et al. (US 2023/0274547 A1)(hereinafter Haim) as applied to claims 1, 10 and 16 above, and further in view of Hamer (US 2016/0155475 A1)(hereinafter Hamer).
Re claim 2, Haim as discussed above in claim 1 discloses all the claimed limitations but fails to explicitly teach wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face. However, the reference of Hamer explicitly teaches wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face (see ¶ 110 for trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face (i.e. a police officer or other person can then review each video clip and create a file or structure containing the video clips of interest, four segments involving a particular face corresponding to Recognized Faces data 2301 (e.g., the name “Joe Smith”) are detected, the video clip corresponding to Segment ID 2372 shows a close-up shot of the perpetrator as described in fig. 23 paragraph 110). Also, see fig. 2 paragraphs 70, 87)
Therefore, taking the combined teachings of Haim and Hamer as a whole, it would have been obvious before the effective filing date of the claimed invention to incorporate this feature (close up of a face) into the system of Haim as taught by Hamer.
One will be motivated to incorporate the above feature into the system of Haim as taught by Hamer for the benefit of identifying all video clips containing the face of interest (e.g., all video clips with “Joe Smith” listed in the Recognized Faces field of Other Metadata 2000), wherein a police officer or other person can then review each video clip and create a file or structure containing the video clips of interest, wherein in FIG. 23, four segments involving a particular face corresponding to Recognized Faces data 2301 (e.g., the name “Joe Smith”) are detected, wherein the video clip corresponding to Segment ID 2311 shows the perpetrator entering a building, wherein the video clip corresponding to Segment ID 2325 shows the perpetrator walking at a train station, wherein the video clip corresponding to Segment ID 2301 shows the perpetrator driving car, wherein the video clip corresponding to Segment ID 2372 shows a close-up shot of the perpetrator in order to ease the processing time when recognizing a face of a perpetrator (see fig. 23 ¶ 110)
Re claim 3, Haim as discussed above in claim 1 discloses all the claimed limitations but fails to explicitly teach wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face as well as including speech. However, the reference of Hamer explicitly teaches wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face as well as including speech (see ¶ 110 for trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a close up of a face as well as including speech (i.e. server 30 identifies all video streams, video segments, and/or video clips that contain a match for the image of the face, and/or identifies all audio streams, audio segments, and/or audio clips that contain a match for the voice recording (step 1225) as described in fig. 19 paragraph 96, furthermore, a police officer or other person can then review each video clip and create a file or structure containing the video clips of interest, four segments involving a particular face corresponding to Recognized Faces data 2301 (e.g., the name “Joe Smith”) are detected as described in fig. 23 paragraph 110). Also, see fig. 2 paragraphs 70, 87)
Therefore, taking the combined teachings of Haim and Hamer as a whole, it would have been obvious before the effective filing date of the claimed invention to incorporate this feature (close up of a face) into the system of Haim as taught by Hamer.
Per claim 3, Haim and Hamer are combined for the same motivation as set forth in claim 2 above.
Re claim 4, Haim as discussed above in claim 1 discloses all the claimed limitations but fails to explicitly teach further comprising: performing facial recognition to identify a portion of the video file that includes a face of a specific user of a device. However, the reference of Hamer explicitly teaches further comprising: performing facial recognition to identify a portion of the video file that includes a face of a specific user of a device (see ¶ 110 for performing facial recognition to identify a portion of the video file that includes a face of a specific user of a device (i.e. after the facial recognition algorithm is run, all video clips containing the face of interest (e.g., all video clips with “Joe Smith” listed in the Recognized Faces field of Other Metadata 2000) can be identified and shown in the video editing platforms previously described as shown in fig. 23 paragraph 110). Also, see figs. 9, 20 paragraphs 45, 103, 108)
Therefore, taking the combined teachings of Haim and Hamer as a whole, it would have been obvious before the effective filing date of the claimed invention to incorporate this feature (facial recognition) into the system of Haim as taught by Hamer.
One will be motivated to incorporate the above feature into the system of Haim as taught by Hamer for the benefit of identifying all video clips containing the face of interest (e.g., all video clips with “Joe Smith” listed in the Recognized Faces field of Other Metadata 2000), wherein a police officer or other person can then review each video clip and create a file or structure containing the video clips of interest, wherein in FIG. 23, four segments involving a particular face corresponding to Recognized Faces data 2301 (e.g., the name “Joe Smith”) are detected, wherein the video clip corresponding to Segment ID 2311 shows the perpetrator entering a building, wherein the video clip corresponding to Segment ID 2325 shows the perpetrator walking at a train station, wherein the video clip corresponding to Segment ID 2301 shows the perpetrator driving car, wherein the video clip corresponding to Segment ID 2372 shows a close-up shot of the perpetrator in order to ease the processing time when recognizing a face of a perpetrator (see fig. 23 ¶ 110)
Re claim 5, the combination of Haim and Hamer as discussed above in claim 4 discloses all the claimed limitations but fails to explicitly teach wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the specific user of the device. However, the reference of Hamer explicitly teaches wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the specific user of the device (see ¶ 110 for trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the specific user of the device (i.e. after the facial recognition algorithm is run, all video clips containing the face of interest (e.g., all video clips with “Joe Smith” listed in the Recognized Faces field of Other Metadata 2000) can be identified and shown in the video editing platforms previously described as shown in fig. 23 paragraph 110). Also, see figs. 9, 20 paragraphs 45, 103, 108)
Therefore, taking the combined teachings of Haim and Hamer as a whole, it would have been obvious before the effective filing date of the claimed invention to incorporate this feature (face of the specific user of the device) into the system of Haim as taught by Hamer.
One will be motivated to incorporate the above feature into the system of Haim as taught by Hamer for the benefit of depicting examples of Other Metadata 2000, wherein other Metadata 2000 can be stored in data structure 1000 in the “other metadata” field described above with reference to FIG. 10, wherein here, Other Metadata 2000 can comprise Source ID, Source Category ID, Direction, Speed of Movement, Other Devices in Area, Recognized Faces, Recognized Sounds, and Other, wherein Source ID can be an identifier for a camera, Source Category can be the type of camera, Direction indicates the direction of movement of the camera, Speed of Movement indicates the speed of movement of the camera, Other Devices in Area indicates the Source IDs for other devices that were detected in the area at the time of video capture, or which are later determined to have been in that area at the time of video capture, Recognized Faces can be data indicating the identity of a person who is recognized as a result of a facial recognition algorithm, Recognized Sounds can be a description or identifier for a sound (such as a voice) that is recognized as a result of a sound recognition algorithm, and Other can store other data of interest in order to ease the processing time when indicating the identity of a person who is recognized as a result of a facial recognition algorithm (see fig. 20 ¶ 103)
Re claim 6, Haim as discussed above in claim 1 discloses all the claimed limitations but fails to explicitly teach further comprising: performing facial recognition to identify a portion of the video file that includes a face of a person having a relationship with a specific user of a device. However, the reference of Hamer explicitly teaches further comprising: performing facial recognition to identify a portion of the video file that includes a face of a person having a relationship with a specific user of a device (see ¶ 110 for performing facial recognition to identify a portion of the video file that includes a face of a person having a relationship with a specific user of a device (i.e. after the facial recognition algorithm is run, all video clips containing the face of interest (e.g., all video clips with “Joe Smith” listed in the Recognized Faces field of Other Metadata 2000) can be identified and shown in the video editing platforms previously described as shown in fig. 23 paragraph 110). Also, see figs. 9, 20 paragraphs 45, 103, 108)
Therefore, taking the combined teachings of Haim and Hamer as a whole, it would have been obvious before the effective filing date of the claimed invention to incorporate this feature (facial recognition) into the system of Haim as taught by Hamer.
Per claim 6, Haim and Hamer are combined for the same motivation as set forth in claim 4 above.
Re claim 7, the combination of Haim and Hamer as discussed above in claim 6 discloses all the claimed limitations but fails to explicitly teach wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the person having the relationship with the specific user of the device. However, the reference of Hamer explicitly teaches wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the person having the relationship with the specific user of the device (see ¶ 110 for trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including the face of the person having the relationship with the specific user of the device (i.e. after the facial recognition algorithm is run, all video clips containing the face of interest (e.g., all video clips with “Joe Smith” listed in the Recognized Faces field of Other Metadata 2000) can be identified and shown in the video editing platforms previously described as shown in fig. 23 paragraph 110). Also, see figs. 9, 20 paragraphs 45, 103, 108)
Therefore, taking the combined teachings of Haim and Hamer as a whole, it would have been obvious before the effective filing date of the claimed invention to incorporate this feature (face of the specific user of the device) into the system of Haim as taught by Hamer.
Per claim 7, Haim and Hamer are combined for the same motivation as set forth in claim 5 above.
Re claim 8, Haim as discussed above in claim 1 discloses all the claimed limitations but fails to explicitly teach wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a face, as well as a caption. However, the reference of Hamer explicitly teaches wherein trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a face, as well as a caption (see ¶ 110 for trimming the video file comprises trimming the video file to generate a video clip of the second length based on the video file including a face, as well as a caption (i.e. a police officer or other person can then review each video clip and create a file or structure containing the video clips of interest, four segments involving a particular face corresponding to Recognized Faces data 2301 (e.g., the name “Joe Smith”) are detected, the video clip corresponding to Segment ID 2311 shows the perpetrator entering a building, the video clip corresponding to Segment ID 2325 shows the perpetrator walking at a train station, the video clip corresponding to Segment ID 2301 shows the perpetrator driving car, the video clip corresponding to Segment ID 2372 shows a close-up shot of the perpetrator as described in fig. 23 paragraph 110). Also, see fig. 2 paragraphs 70, 87)
Therefore, taking the combined teachings of Haim and Hamer as a whole, it would have been obvious before the effective filing date of the claimed invention to incorporate this feature (a face, as well as a caption) into the system of Haim as taught by Hamer.
One will be motivated to incorporate the above feature into the system of Haim as taught by Hamer for the benefit of identifying all video clips containing the face of interest (e.g., all video clips with “Joe Smith” listed in the Recognized Faces field of Other Metadata 2000), wherein a police officer or other person can then review each video clip and create a file or structure containing the video clips of interest, wherein in FIG. 23, four segments involving a particular face corresponding to Recognized Faces data 2301 (e.g., the name “Joe Smith”) are detected, wherein the video clip corresponding to Segment ID 2311 shows the perpetrator entering a building, wherein the video clip corresponding to Segment ID 2325 shows the perpetrator walking at a train station, wherein the video clip corresponding to Segment ID 2301 shows the perpetrator driving car, wherein the video clip corresponding to Segment ID 2372 shows a close-up shot of the perpetrator in order to ease the processing time when recognizing a face of a perpetrator (see fig. 23 ¶ 110)
Re claim 11, the combination of Haim and Hamer as discussed above in claim 2 discloses all the claimed limitations of claim 11.
Re claim 12, the combination of Haim and Hamer as discussed above in claim 3 discloses all the claimed limitations of claim 12.
Re claim 13, the combination of Haim and Hamer as discussed above in claim 5 discloses all the claimed limitations of claim 13.
Re claim 14, the combination of Haim and Hamer as discussed above in claim 7 discloses all the claimed limitations of claim 14.
Re claim 17, the combination of Haim and Hamer as discussed above in claim 2 discloses all the claimed limitations of claim 17.
Re claim 18, the combination of Haim and Hamer as discussed above in claim 3 discloses all the claimed limitations of claim 18.
Re claim 19, the combination of Haim and Hamer as discussed above in claims 4 and 5 discloses all the claimed limitations of claim 19.
Re claim 20, the combination of Haim and Hamer as discussed above in claims 6 and 7 discloses all the claimed limitations of claim 20.
Claims 9 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Haim et al. (US 2023/0274547 A1)(hereinafter Haim) as applied to claims 1, 10 and 16 above, and further in view of BLONG et al. (US 2017/0017658 A1)(hereinafter BLONG).
Re claim 9, the combination of Haim and Hamer as discussed above in claim 1 discloses all the claimed limitations but fails to explicitly teach further comprising: creating a video montage file by adding a plurality of video clips from the collection of video clips together; and adding an audio track to the video montage file. However, the reference of BLONG explicitly teaches further comprising: creating a video montage file by adding a plurality of video clips from the collection of video clips together (see ¶ 106 for creating a video montage file by adding a plurality of video clips from the collection of video clips together (i.e. assume a user of user device 210 desires to obtain a single media file by combining media files, related to a search term provided by the user (e.g., the user desires a video montage combining video clips related to dogs) as described in fig. 7 paragraph 103)); and adding an audio track to the video montage file (see fig. 7 ¶ 103 for adding an audio track to the video montage file (i.e. MCC server 230 may add audio to the single media file as described in fig. 2 paragraph 98). Also, paragraph 106)
Therefore, taking the combined teachings of Haim and BLONG as a whole, it would have been obvious before the effective filing date of the claimed invention to incorporate this feature (video montage file) into the system of Haim as taught by BLONG.
One will be motivated to incorporate the above feature into the system of Haim as taught by BLONG for the benefit of having a MCC server 230 that automatically combines the media files, identified for the set of media files, to create a single media file (e.g., combining the video clip entitled “Dog Catches Frisbee” and 10 seconds in length, the video clip entitled “Dog Show Winner” and 10 seconds in length, and the video clip entitled “Dog at Groomers” and 10 seconds in length, to create a single video montage, 30 seconds in length, related to dogs) in order to ease the processing time when automatically creating a single video montage (see fig. 7 ¶ 106)
Re claim 15, the combination of Haim and BLONG as discussed above in claim 9 discloses all the claimed limitations of claim 15.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSE M MESA whose telephone number is (571)270-1706. The examiner can normally be reached Monday-Friday 8:30AM-6:00PM ET.
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5/27/2026
/JOSE M. MESA/
Examiner
Art Unit 2484
/THAI Q TRAN/Supervisory Patent Examiner, Art Unit 2484
Prosecution Insights