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 .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-9, 12-20 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Independent claims 1 and 18 recite “identify an object in a respective frame of video data using an artificial intelligence (AI) model trained on object detection, flag the object for redaction from the video data, identify a moving portion in the respective frame of the video data, the moving portion including at least one pixel having motion in a plurality of frames of the video data, wherein the moving portion is included in a portion of the video data not having the object flagged for redaction, perform a motion analysis of the moving portion of the video data, and based on a result of the motion analysis, flag the moving portion for redaction from the video data” which fall under the grouping of Mental Processes because a person can visually inspect or analyze a video to identify and flag objects, including observing and analyzing motion to identify or flag moving objects for redaction. The use of artificial intelligence to detect an object is described at a high level of generality and merely confines the use of the use of an abstract idea to a particular technological environment (artificial intelligence) and thus fails to add an inventive concept to the claims. The claim further recites “obtain video data” which is merely a data gathering step which is an insignificant extra solution activity. The processor is a generic computer used to perform the abstract idea.
Dependent claim 2 recites “the motion analysis includes determining whether an area of the moving portion in the respective frame of the video data is less than a threshold area, and the electronic processor is configured to, in response to determining that the area of the moving portion in the respective frame of the video data is less than a threshold area, flag the moving portion for redaction from the video data” which falls under the grouping of Mental Processes because a person can visually observe a video to detect or flag an object and visually analyze the motion of an object and mentally estimate a size of the object.
Dependent claim 3 recites “in response to determining that the area of the moving portion in the respective frame of the video data is not less than a threshold area, flag an edge portion of the respective frame for redaction from the video data” falls under the grouping of Mental Processes because a person can visually observe a video and identify or flag an object for redaction.
Dependent claim 4 recites “wherein the electronic processor is further configured to determine the threshold area by dynamically selecting a threshold area ratio that is a ratio of the threshold area to a total area of the respective frame based on at least one selected from the group consisting of: an area of moving portions included in identified objects exceeding a threshold, and a total number of identified objects in the respective frame exceeding a threshold number of objects” which falls under the grouping of Mental Processes because a person can mentally select a threshold and mentally perform the mathematical operation of calculating ratios. Alternatively, the limitation falls under the grouping of Mathematical calculations.
Dependent claim 5 recites “the motion analysis includes determining whether the moving portion in the respective frame of the video data has a consistency with a corresponding moving portion in a previous frame of the video data, and the electronic processor is configured to, in response to determining that the moving portion in the respective frame of the video data has a consistency with a corresponding moving portion in a previous frame of the video data, flag the moving portion for redaction from the video data” falls under the grouping of Mental Processes because a person can visually observe the video and analyze the motion across frames to determine a consistency and to identify or flag an object for redaction.
Dependent claim 6 recites “wherein the consistency includes a consistency in area size of the moving portion” which falls under the grouping of Mental Processes because a person can visually observe the video and estimate or calculate object size and determine the consistency of size across temporal frames.
Dependent claim 7 recites “wherein the consistency is determined using pixel-differencing with respect to the moving portion in the respective frame of the video data and a previous frame of the video data” which falls under the grouping of Mathematical calculation because pixel differencing is a mathematical operation.
Dependent claim 8 recites “wherein the consistency includes a consistency in trajectory of the moving portion” which falls under the grouping of Mental Processes because a person can visually observe the video and determine the trajectory or direction of motion and its consistency across temporal frames.
Dependent claim 9 recites “the motion analysis includes determining a compactness of the moving portion in the respective frame of the video data, and the electronic processor is configured to flag the moving portion for redaction from the video data based on the compactness” which falls under the grouping of Mental Processes because a person can visually observe the video and determine shape or compactness consistency across temporal frames and to identify or flag an object for redaction.
Dependent claim 12 recites “determine whether the object is a tracked object having been detected in a previous frame of video data, and flag the object for redaction from the video data in response to determining that the object is a tracked object” which falls under the grouping of Mental Processes because a person can visually observe the video and track an object across frames and identify an object for redaction.
Dependent claim 13 recites “flag an edge portion of the respective frame for redaction from the video data” which falls under the grouping of Mental Processes because a person can visually observe the video and identify an edge or object to be redacted.
Dependent claim 14 recites “provide a redacted video stream of the video data to a graphical user interface (GUI) of the display device, and responsive to verifying a user permission associated with a user of the display device, provide an at least partially unredacted video stream of the video data to the GUI” which is merely a data output step which is an insignificant extra solution activity.
Dependent claim 15 recites “wherein the object detection is performed with respect to a set of target object types” which falls under the grouping of Mental Processes because a person can visually observe the video to identify or detect different classes of objects.
Dependent claim 16 recites “wherein the moving portion includes at least one pixel” which merely describes that the video data comprises pixels.
Dependent claim 17 recites “further comprising a video camera configured to obtain the video data” which is merely a data gathering step using a camera, which is an insignificant extra solution activity.
With regard to claims 19-20, see discussion of claims 2-3, respectively.
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 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(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, 10-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by D1.1
With regard to claim 1, D1 teach an electronic processor configured to: obtain video data (see ¶ 12, fig. 4: retrieve video), identify an object in a respective frame of video data using an artificial intelligence (AI) model trained on object detection (see ¶ 15, fig. 4: identify object to be redacted; ¶ 24: AI used to detect object), flag the object for redaction from the video data (see ¶ 15: identifying objects read as flagging; see also ¶ 36: objects are marked up, also read as flagging objects), identify a moving portion in the respective frame of the video data, the moving portion including at least one pixel having motion in a plurality of frames of the video data, wherein the moving portion is included in a portion of the video data not having the object flagged for redaction (see ¶ 41, fig. 4: moving reflective object identified or flagged for redaction), perform a motion analysis of the moving portion of the video data (see ¶ 41: analyzing movement of reflective surface, checks to see if it moves simultaneously with object), and based on a result of the motion analysis, flag the moving portion for redaction from the video data (see ¶ 41, fig. 4: identifies or flags corresponding moving reflective surface to redact).
With regard to claim 10, D1 teach the identifying of an object in a respective frame of video data includes determining a confidence level associated with a detection of the object, and the electronic processor is configured to flag the object for redaction from the video data in response to the confidence level exceeding a threshold confidence level (see ¶¶ 28-31: confidence values).
With regard to claim 11, D1 teach the threshold confidence level is a first threshold confidence level that is less than a second confidence level used for an object detection in video analysis processes other than video redaction (see ¶¶ 31, 34: plurality of confidence score thresholds and ranges, ¶ 34: upper and lower confidence score thresholds).
With regard to claim 12, D1 teach the electronic processor is configured to determine whether the object is a tracked object having been detected in a previous frame of video data, and flag the object for redaction from the video data in response to determining that the object is a tracked object (see ¶ 41: detecting and tracking objects across frames).
With regard to claim 13, D1 teach wherein the electronic processor is configured to flag an edge portion of the respective frame for redaction from the video data (see ¶ 15: identifying objects read as flagging; see also ¶ 36: objects are marked up, also read as flagging objects; the objects maybe located anywhere in the frame including the edge portions).
With regard to claim 14, D1 teach wherein the electronic processor is communicatively connected to a display device, and the electronic processor is further configured to: provide a redacted video stream of the video data to a graphical user interface (GUI) of the display device and responsive to verifying a user permission associated with a user of the display device, provide an at least partially unredacted video stream of the video data to the GUI (see ¶¶ 33, 35: displaying video; see ¶¶ 23, 51-52: user selection to identify which objects to redact and by extension which objects not to redact).
With regard to claim 15, D1 teach wherein the object detection is performed with respect to a set of target object types (see ¶ 27: classes of objects).
With regard to claim 16, D1 teach wherein the moving portion includes at least one pixel (see ¶ 41, fig. 4: moving reflective object identified or flagged for redaction, includes at least one pixel).
With regard to claim 17, D1 teach further comprising a video camera configured to obtain the video data (see abstract: video camera).
With regard to claim 18, see discussion of claim 1.
With regard to claim 19, see discussion of claim 2.
With regard to claim 20, see discussion of claim 3.
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 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 5-9 are rejected under 35 U.S.C. 103 as being unpatentable over D1 and further in view of D2.2
With regard to claim 5, D1 fails to explicitly teach the motion analysis includes determining whether the moving portion in the respective frame of the video data has a consistency with a corresponding moving portion in a previous frame of the video data, and the electronic processor is configured to, in response to determining that the moving portion in the respective frame of the video data has a consistency with a corresponding moving portion in a previous frame of the video data, flag the moving portion for redaction from the video data, however D2 teaches the missing feature (see fig. 4, col 6 lines 45-65: shape consistency).
One skilled in the art before the effective filing date would have found it obvious to combine the teachings to arrive at the claimed invention. D1 teaches tracking a detected object to redact. Meanwhile, D2 teaches using shape or size consistency to verify that the tracked object is the same object across frames. It would have thus been obvious to incorporate known teachings of D2 into the configuration of D1 in order to track an object and to ensure that the same object is being tracked across frames by utilizing consistency metrics yielding predictable and enhanced results.
With regard to claim 6, D2 teach wherein the consistency includes a consistency in area size of the moving portion (see fig. 4, col 7 lines 55-65: size consistency). The motivation for combining the references is the same as stated above.
With regard to claim 7, D2 teach wherein the consistency is determined using pixel-differencing with respect to the moving portion in the respective frame of the video data and a previous frame of the video data (see col 7 lines 5-15: frame to frame differences). The motivation for combining the references is the same as stated above.
With regard to claim 8, D2 teach wherein the consistency includes a consistency in trajectory of the moving portion (see fig. 4, col 10 lines 45-60: direction of motion consistency metric). The motivation for combining the references is the same as stated above.
With regard to claim 9, D2 teach the motion analysis includes determining a compactnesssee fig. 4, col 6 lines 50-65: shape consistency read as compactness). The motivation for combining the references is the same as stated above.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over D1.
With regard to claim 2, D1 fails to explicitly teach the motion analysis includes determining whether an area of the moving portion in the respective frame of the video data is less than a threshold area, and the electronic processor is configured to, in response to determining that the area of the moving portion in the respective frame of the video data is less than a threshold area, flag the moving portion for redaction from the video data. However, Examiner takes Official Notice to the fact that filtering out objects based on size threshold is extremely well known in the art before the effective filing date and one skilled in the art would have been motivated to incorporate known teachings into the configuration of D1 yielding predictable and enhanced results. The motivation would have been to eliminate or redact small objects which may for example be noise or unimportant objects that are of no interest for a user.
Claims 3, 4 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.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AVINASH YENTRAPATI whose telephone number is (571)270-7982. The examiner can normally be reached on 8AM-5PM.
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/AVINASH YENTRAPATI/Primary Examiner, Art Unit 2672
1 US Publication No. 2024/0087282.
2 US Patent No. 7,391,907.
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