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 conflicting claims 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); 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 nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined 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 § 2146 et seq. 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 filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1, 10 and 18 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 9 and 17 of U.S. Patent No. 11,941,816 (hereinafter ‘816). Although the claims at issue are not identical, they are not patentably distinct from each other because:
Current Application ‘816
Claim 1:
receiving digital media arranged as a sequence of video frames;
generating, for each video frame of the sequence of video frames, a first set of runtime cropping characteristics, including first cropping coordinates for the video frame corresponding to a first cropped version of the video frame; and
storing at least one video frame of the sequence of video frames and the associated first set of runtime cropping characteristics,
wherein, prior to receiving the sequence of video frames, implementing a training operation to predict cropping characteristics for each training raw image of a plurality of training raw images, based on expected cropping characteristics represented in a set of training master images associated with the training raw image,
and
wherein each training master image of the set of training master images indicates cropping characteristics defined for the associated respective training raw image.
Claim 17:
receiving one or more uncropped images;
applying the ML predictor program to the one or more uncropped images in order to generate for each respective uncropped image of the one or more uncropped images a respective set of runtime cropping characteristics, wherein the respective set of runtime cropping characteristics for each respective uncropped image comprises one or more subsets of cropping coordinates for the respective uncropped image, and wherein each subset corresponds to a different cropped version of the respective uncropped image; and
storing, in non-transitory computer-readable memory, the one or more uncropped images together with the respective set of runtime cropping characteristics for each respective uncropped image of the one or more uncropped images,
wherein, prior to receiving the one or more uncropped images, the ML predictor program has been trained to predict cropping characteristics for each respective training raw image of a plurality of training raw images, based on expected cropping characteristics represented in a respective set of training master images associated with the respective training raw image, and
wherein each training master image of the respective set of training master images indicates respective cropping characteristics defined for the associated respective training raw image.
Current Application ‘816
Claim 10:
a processor; and
a memory storing instructions that, when executed by the processor implements the operations of a machine learning (ML) predictor program, wherein the operations include:
receiving digital media arranged as a sequence of video frames;
generating, for each video frame of the sequence of video frames, a first set of runtime cropping characteristics, including first cropping coordinates for the video frame corresponding to a first cropped version of the video frame; and
storing at least one video frame of the sequence of video frames and the associated first set of runtime cropping characteristics,
wherein, prior to receiving the sequence of video frames, implementing a training operation to predict cropping characteristics for each training raw image of a plurality of training raw images, based on expected cropping characteristics represented in a set of training master images associated with the training raw image,
and
wherein each training master image of the set of training master images indicates cropping characteristics defined for the associated respective training raw image.
Claim 9:
one or more processors; and
memory storing instructions that, when executed by the one or more processors, cause the system to carry out operations of a machine learning (ML) predictor program, wherein the operations include:
receiving one or more uncropped images;
applying the ML predictor program to the one or more uncropped images in order to generate for each respective uncropped image of the one or more uncropped images a respective set of runtime cropping characteristics, wherein the respective set of runtime cropping characteristics for each respective uncropped image comprises one or more subsets of cropping coordinates for the respective uncropped image, and wherein each subset corresponds to a different cropped version of the respective uncropped image; and
storing, in non-transitory computer-readable memory, the one or more uncropped images together with the respective set of runtime cropping characteristics for each respective uncropped image of the one or more uncropped images,
wherein, prior to receiving the one or more uncropped images, the ML predictor program has been trained to predict cropping characteristics for each respective training raw image of a plurality of training raw images, based on expected cropping characteristics represented in a respective set of training master images associated with the respective training raw image, and
wherein each training master image of the respective set of training master images indicates respective cropping characteristics defined for the associated respective training raw image.
Current Application ‘816
Claim 18:
receiving digital media arranged as a sequence of video frames;
generating, for each video frame of the sequence of video frames, a first set of runtime cropping characteristics, including first cropping coordinates for the video frame corresponding to a first cropped version of the video frame; and
storing at least one video frame of the sequence of video frames and the associated first set of runtime cropping characteristics,
wherein, prior to receiving the sequence of video frames, implementing a training operation to predict cropping characteristics for each training raw image of a plurality of training raw images, based on expected cropping characteristics represented in a set of training master images associated with the training raw image,
and
wherein each training master image of the set of training master images indicates cropping characteristics defined for the associated respective training raw image.
Claim 1:
receiving one or more uncropped images by the computing device;
applying the ML predictor program to the one or more uncropped images in order to generate for each respective uncropped image of the one or more uncropped images a respective set of runtime cropping characteristics, wherein the respective set of runtime cropping characteristics for each respective uncropped image comprises one or more subsets of cropping coordinates for the respective uncropped image, and wherein each subset corresponds to a different cropped version of the respective uncropped image; and
storing, in non-transitory computer-readable memory, the one or more uncropped images together with the respective set of runtime cropping characteristics for each respective uncropped image of the one or more uncropped images,
wherein, prior to receiving the one or more uncropped images, the ML predictor program has been trained to predict cropping characteristics for each respective training raw image of a plurality of training raw images, based on expected cropping characteristics represented in a respective set of training master images associated with the respective training raw image, and
wherein each training master image of the respective set of training master images indicates respective cropping characteristics defined for the associated respective training raw image.
Claims 2-9, 11-17 and 19-20 of the current application do not correspond to any claims of ‘816.
Allowable Subject Matter
Claims 2-9, 11-17 and 19-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and provided that the Double Patenting Rejection is overcome.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHARLOTTE M BAKER whose telephone number is (571)272-7459. The examiner can normally be reached Mon - Fri 8:00-5:00.
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/CHARLOTTE M BAKER/Primary Examiner, Art Unit 2664
08 October 2026
