DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-18 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2, 7-14, 16-18 is/are rejected under 35 U.S.C. 103 as obvious over Thornton et al. (US2013/0155229) in view of Chen et al. (US2016/0012647).
To claim 1, Thornton teach an apparatus comprising at least one processor; and at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to:
receive images of a video sequence for object detection (Figs. 10, 12, 18; paragraph 0066);
search an object from the received images (paragraphs 0055-0058);
define a bounding box around a detected object in the received images (paragraphs 67, 0072, 0074, 0077, 0084);
calculate mean and covariance to the detected object (paragraphs 0088 ,0091, 0112, mean expected position set and covariance matrix of position changes due to body, clothing, and view angle variation are obviously with respect to detected object/person);
determine, based on the mean and covariance, a position of at least one of the following: the apparatus, the detected object, or an image capturing device (paragraphs 0088-0091, 0111-0113); and
determine a drift error of the determined position (paragraphs 0072, 0075, 0077).
But, Thornton do not expressly disclose calculating mean and covariance based on bounding box sizes of the detected object in the received images.
Chen teach determining positions and sizes of cases of the inspected object from the opaque parts of the volume data (paragraphs 0016, 0078), wherein a minimal size of a bounding box which bounds an object in the direction, wherein the position and direction of the bounding box are calculated using statistics of first-order moment (mean value) and second-order moment (covariance matrix) (paragraphs 0101-0104).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Chen into the apparatus of Thornton, in order to further bounding box position determination by design preference.
To claim 13, Thornton and Chen teach a method performed by an apparatus (as explained in response to claim 1 above).
To claim 18, Thornton and Chen teach a non-transitory computer readable medium having stored thereon a set of computer readable instructions that, when executed by at least one processor, cause an apparatus (as explained in response to claim 1 above).
To claims 2 and 14, Thornton and Chen teach claims 1 and 13.
Thornton teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus to: recognize the object in the bounding boxes (paragraphs 0005, 0074, 0099).
To claims 7 and 16, Thornton and Chen teach claims 1 and 13.
Thornton teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: search a plurality of objects; and define bounding boxes around all detected objects (Fig. 2).
To claims 8 and 17, Thornton and Chen teach claims 7 and 16.
Thornton teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: examine from the plurality of images which bounding boxes represent a same object (paragraphs 0082, 0099, tracking the same person across observations); and use those bounding boxes representing the same object to calculate the mean and covariance for that object (paragraph 0088, obvious as the mean expected position set and the covariance matrix of position changes due to body, clothing, and view angle variation, which is to track the same object).
To claim 9, Thornton and Chen teach claim 1.
Thornton teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: compare the area within the bounding box of the object with a plurality of image information obtained by an image learning process of a neural network; and select a class for the object based on the image information which produced highest likelihood of match or which produced a likelihood of match greater than a threshold (paragraphs 0058, 0063, 0096, 0099, machine learning; paragraphs 0077-0079, 0122, detection threshold, wherein implementing neural network in image processing and object detection is well-known in the art of machine learning, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate by design preference, hence Official Notice is taken).
.
To claim 10, Thornton and Chen teach claim 1.
Thornton teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: enter the received images to a neural network; execute the neural network to recognize the object; output from the neural network at least one of a likelihood of a match or a likelihood of not a match regarding the object (as explained in response to claim 9 above, wherein implementation and operation of neural network would be obvious).
To claim 11, Thornton and Chen teach claim 1.
Thornton teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: use dimensions of the bounding box and dimensions of the object to determine a current location of an object of interest (paragraph 0067).
To claim 12, Thornton and Chen teach claim 11.
Thornton teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: determine the location at intervals based on a plurality of images of the video sequence; and use the locations determined at intervals to find out a travelling route of the object of interest (paragraphs 0016-0017, 0023, 0027, 0071).
Claim(s) 3, 15 is/are rejected under 35 U.S.C. 103 as obvious over Thornton et al. (US2013/0155229) in view of Chen et al. (US2016/0012647) and Behrendt (US2020/0349365).
To claims 3 and 15, Thornton and Chen teach claims 2 and 13.
But, Thornton and Chen do not expressly disclose said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus to determine the position of the apparatus by: determining distances from the apparatus or the image capturing device to the detected object.
However, Chen does teach distance from the viewpoint to a point farthest to the viewpoint in a certain direction (paragraph 0097)
Behrendt teach determining distances from the apparatus or the image capturing device to the detected object (paragraph 0028), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the apparatus of Thornton and Chen, in order to provide distance measurement.
Claim(s) 4-6 is/are rejected under 35 U.S.C. 103 as obvious over Thornton et al. (US2013/0155229) in view of Chen et al. (US2016/0012647), Behrendt (US2020/0349365) and Kato (US2020/0043188).
To claim 4, Thornton, Chen and Behrendt teach claim 3.
Thornton, Chen and Behrendt teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: maintain a look up table of classes of objects (obvious in paragraph 0060 of Thornton, having classifiers), but Thornton, Chen and Behrendt do not expressly disclose enter in the look up table an actual position of the detected object in a scene where the image representing the object has been captured.
However, Chen does teach performing volume rendering integration on a segment between each two sampling points using a lookup table for pre-integration based on opacity, to obtain opaqueness corresponding to the segment (paragraphs 0023, 0028).
Kato teach having an object information management table to record positions of detected object (Fig. 14; paragraphs 0124-0129), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the apparatus of Thornton, Chen and Behrendt, in order to keep records for reference.
To claim 5, Thornton, Chen, Behrendt and Kato teach claim 4.
Thornton, Chen, Behrendt and Kato teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: compare the image of the object with image information in the look up table comprising classification information of objects and dimensions of objects; use the dimensions and the actual position of the object to determine a distance to the object from a location the image have been captured (obvious in Fig. 14 of Kato).
To claim 6, Thornton, Chen, Behrendt and Kato teach claim 4.
Thornton, Chen, Behrendt and Kato teach said at least one memory storing instructions that, when executed by the at least one processor, cause the apparatus at least to: identify the object based on the look up table to find out physical dimensions of the recognized object; map the obtained physical dimensions with the dimensions of the objects in pixels based on the bounding box which have been formed around the image information of the object (obvious in paragraphs 0127, 0275 of Kato, which obviously correspond to bounding box of Thornton).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHIYU LU whose telephone number is (571)272-2837. The examiner can normally be reached Weekdays: 8:30AM - 5:00PM.
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ZHIYU . LU
Primary Examiner
Art Unit 2669
/ZHIYU LU/Primary Examiner, Art Unit 2665 February 1, 2026
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