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 § 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)(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.
Claim(s) 1, 2, 13, 18, 19 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhou et al. (U.S. Patent Application 20110228982).
In regards to claim 1, Zhou teaches an image processing apparatus [Fig. 1; e.g. information processing device, 0024] comprising:
one or more memories [e.g. storage medium, 0013] storing instructions [e.g. program, 0013]; and
one or more processors [e.g. computer inherently comprises at least one processor, 0013] executing the instructions to:
obtain three-dimensional shape data of at least one object [e.g. recognize a shape of the tracked object which is disposed in a three-dimensional space, 0025], wherein the three-dimensional shape data is generated using images of the at least one object captured from a plurality of directions by a plurality of image capturing units [Fig. 1; e.g. The learning image Is is an image in which a tracked object O is captured on different shooting conditions (a shooting distance, a shooting angle, and the like from each of the cameras of the learning image input unit 11) shown by the label, 0025];
extract a plurality of parts [Fig. 5; e.g. part of palm, part of thumb, part of middle finger, 0039] of the obtained three-dimensional shape data;
assign identifiers [e.g. labels, 0040] to the extracted plurality of parts based on positions [e.g. based on the shooting condition such as position, 0040-0041, 0043] of the extracted plurality of parts; and
track the extracted plurality of parts based on the identifiers and the positions of the extracted plurality of parts [Fig. 6A, 6B; e.g. tracking the features of the tracked object based on the labels and positions of the features, 0030-0032, 0052-0055].
In regards to claim 2, Zhou teaches the image processing apparatus according to claim 1, wherein the one or more processors extract the plurality of parts by clipping some of the three-dimensional shape data [Fig. 5; e.g. The feature filters show parts of the shape of the hand. For example, parts of the palm, thumb, and middle finger, 0039].
In regards to claim 13, Zhou teaches the image processing apparatus according to claim 1, wherein the one or more processors further obtain a virtual viewpoint [e.g. shooting angle, 0025], and wherein the one or more processors generate a virtual viewpoint image [Fig. 6A-6B; e.g. tracking image, 0054-0055] based on the virtual viewpoint, the three-dimensional shape data, and a result of the tracking [e.g. based on the shooting angle, the shape of the tracked object, and the learning result of the tracking, 0025, 0054-0057].
In regards to claim 18, the claims recite similar limitations as claim 1, but in method form. Therefore, the same rationale as claim 1 is applied.
In regards to claim 19, the claims recite similar limitations as claim 1, but in the form of a non-transitory computer-readable storage medium storing a program for causing a computer to perform the steps of claim 1. Furthermore, Zhou teaches a non-transitory computer-readable storage medium [e.g. storage medium, 0013] storing a program [e.g. program, 0013] for causing a computer [e.g. computer, 0013] to perform the steps of claim 1. Therefore, the same rationale as claim 1 is applied.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al. (U.S. Patent Application 20110228982) as applied to claim 1 above, and further in view of Luo et al. (U.S. Patent Application 20210049802).
In regards to claim 3, Zhou does not explicitly teach the image processing apparatus according to claim 1, wherein the one or more processors extract the plurality of parts corresponding to feet in the three-dimensional shape data.
However, Luo teaches the image processing apparatus according to claim 1, wherein the one or more processors [e.g. processor, 0005] extract the plurality of parts corresponding to feet in the three-dimensional shape data [Fig. 9B; e.g. separating the different body parts such as feet in the rigged 3D scan, 0131, also see 0128].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Zhou’s method with the features of wherein the one or more processors extract the plurality of parts corresponding to feet in the three-dimensional shape data in the same conventional manner as taught by Luo because segmentation of 3D features is a well known process and commonly used in the art of computer graphical systems [0099].
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al. (U.S. Patent Application 20110228982) as applied to claim 1 above, and further in view of Miyano et al. (U.S. Patent Application 20160162738).
In regards to claim 4, Zhou does not explicitly teach the image processing apparatus according to claim 1, the one or more processors further execute the instructions to calculate a representative position of parts, among the extracted plurality of parts, to which the same identifier is assigned based on a result of the tracking, and output the representative position as an object position.
However, Miyano teaches the image processing apparatus [e.g. object tracking device, 0113-0114] according to claim 1, the one or more processors [e.g. CPU, 0113-0114] further execute the instructions [e.g. program, 0113-0114] to calculate a representative position of parts [Fig. 10; e.g. barycentric position, 0100], among the extracted plurality of parts [e.g. candidates, 0100], to which the same identifier is assigned [Fig. 1; e.g. the candidates have the same label named cluster 1, 0100-0101] based on a result of the tracking [e.g. based on the results of observing the positions of objects being tracked, 0035-0036], and output the representative position as an object position [e.g. output the calculated position as the object position, 0100-0101].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Zhou’s image processing apparatus with the features of
calculating a representative position of parts, among the extracted plurality of parts, to which the same identifier is assigned based on a result of the tracking, and output the representative position as an object position
in the same conventional manner as taught by Miyano because Miyano provides a method for object tracking where each object can be properly tracked even in the case where objects to be tracked are near each other in an environment in which the number of objects changes with time [0019].
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al. (U.S. Patent Application 20110228982) as applied to claim 1 above, and further in view of Babazaki (U.S. Patent Application 20230326041).
In regards to claim 5, Zhou does not explicitly teach the image processing apparatus according to claim 1, wherein the one or more processors assign an identifier to each of the plurality of parts based on a distance between the plurality of parts of the three-dimensional shape data.
However, Babazaki teaches the image processing apparatus [Fig. 1; e.g. tracking device, 0057] according to claim 1, wherein the one or more processors [Fig. 3B; e.g. processor, 0072] assign an identifier [Fig. 6; e.g. tracking ID, 0104] to each of the plurality of parts [e.g. group of joint points, 0104] based on a distance between the plurality of parts [e.g. based on the sum of distances between the correct answer joint point groups, 0104] of the three-dimensional shape data [e.g. tracking target object, 0104].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Zhou’s image processing apparatus with the features of
assigning an identifier to each of the plurality of parts based on a distance between the plurality of parts of the three-dimensional shape data
in the same conventional manner as taught by Babazaki because assigning tracking IDs to objects is well known and commonly used in the art of object tracking systems [0094].
Claim(s) 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al. (U.S. Patent Application 20110228982) as applied to claim 1 above, and further in view of Masuda (U.S. Patent Application 20240111297).
In regards to claim 6, Zhou does not explicitly teach the image processing apparatus according to claim 1, wherein the one or more processors determine in which circumscribed cuboid in the three-dimensional shape data each of the extracted plurality of parts is included, and assign the same identifier to parts included in the same circumscribed cuboid among the extracted plurality of parts.
However, Masuda teaches the image processing apparatus [Fig. 3; e.g. control device, 0082] according to claim 1, wherein the one or more processors [Fig. 3; e.g. processor, 0093] determine in which circumscribed cuboid in the three-dimensional shape data each of the extracted plurality of parts is included [Fig. 13; e.g. The processor generates a three-dimensional bounding box that encloses representative points belonging to the same group of objects. For example, a row of trees is within a 3D bounding box, 0128], and assign the same identifier to parts included in the same circumscribed cuboid among the extracted plurality of parts [Fig. 13; e.g. the row of trees included in the 3D bounding box are assigned an ID, 0128-0129].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Zhou’s image processing apparatus with the features of
determining in which circumscribed cuboid in the three-dimensional shape data each of the extracted plurality of parts is included, and assign the same identifier to parts included in the same circumscribed cuboid among the extracted plurality of parts
in the same conventional manner as taught by Masuda because bounding boxes are well known and commonly used in the art of object tracking systems [0128].
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al. (U.S. Patent Application 20110228982) as applied to claim 1 above, and further in view of Delp, III et al. (U.S. Patent Application 20230222821, hereafter referred to as Delp).
In regards to claim 7, Zhou does not explicitly teach the image processing apparatus according to claim 1, wherein the one or more processors set a region in which a predetermined identifier is to be assigned, and assign the predetermined identifier to parts included in the region among the extracted plurality of parts.
However, Delp teaches the image processing apparatus [Fig. 17; e.g. computing device, 0155] according to claim 1, wherein the one or more processors [Fig. 17; e.g. one or more processors, 0155] set a region [Fig. 2; e.g. region, 0046] in which a predetermined identifier [e.g. predetermined label, 0039] is to be assigned, and assign the predetermined identifier to parts included in the region among the extracted plurality of parts [Fig. 2; e.g. assigning the predetermined label, chicken wing, to objects included in the image, 0046].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Zhou’s image processing apparatus with the features of
setting a region in which a predetermined identifier is to be assigned, and assign the predetermined identifier to parts included in the region among the extracted plurality of parts
in the same conventional manner as taught by Delp because labeling objects in an image is well known and commonly used in the art of object recognition systems.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al. (U.S. Patent Application 20110228982) as applied to claim 1 above, and further in view of Yokono et al. (U.S. Patent Application 20150120624).
In regards to claim 8, Zhou does not explicitly teach the image processing apparatus according to claim 1, wherein, based on a user's instruction, the one or more processors reassign the identifiers to the extracted plurality of parts to which the identifiers have been assigned.
However, Yokono teaches the image processing apparatus [Fig. 3; e.g. imaging apparatus, 0037] according to claim 1, wherein, based on a user's instruction [e.g. user input, 0073], the one or more processors [Fig. 3; e.g. control unit such as a processor, 0060] reassign the identifiers to the extracted plurality of parts to which the identifiers have been assigned [e.g. relabeling the incorrect images that were assigned incorrect labels, 0073].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Zhou’s image processing apparatus with the features of
wherein, based on a user's instruction, the one or more processors reassign the identifiers to the extracted plurality of parts to which the identifiers have been assigned
in the same conventional manner as taught by Yokono because Yokono provides a method for enhancing the prediction accuracy by using data having consistency of the labels, i.e., high quality data, as the teacher set and the evaluation set [0034].
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al. (U.S. Patent Application 20110228982) as applied to claim 1 above, and further in view of Kilambi et al. (U.S. Patent Application 20080118106).
In regards to claim 11, Zhou does not explicitly teach the image processing apparatus according to claim 1, wherein the one or more processors extract a shape corresponding to a predetermined height from a floor surface of an image capturing region in the three-dimensional shape data.
However, Kilambi teaches the image processing apparatus [Fig. 7; e.g. system, 0147] according to claim 1, wherein the one or more processors [Fig. 7; e.g. processor, 0148] extract a shape [Fig. 3; e.g. elliptical cylinder, 0076, also see claim 13] corresponding to a predetermined height [Fig. 3; e.g. predetermined height, see claim 13, also see 0078] from a floor surface [Fig. 3; e.g. ground plane, see claim 13] of an image capturing region [Fig. 2B; e.g. field of view of the camera, 0047-0051] in the three-dimensional shape data [e.g. three dimensional information, 0047].
Therefore, it would have been obvious to one of ordinary skill in the art to have modified Zhou’s image processing apparatus with the features of
extracting a shape corresponding to a predetermined height from a floor surface of an image capturing region in the three-dimensional shape data
in the same conventional manner as taught by Kilambi because Kilambi provides a method for reducing false detections from other objects commonly found in urban environments and reduces errors caused by shadows on the ground plane [0052].
Allowable Subject Matter
Claims 9, 10, 12, 14-17 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.
In regards to claim 9, the prior art of record fails to teach or suggest the image processing apparatus according to claim 1, wherein the one or more processors project the plurality of parts onto a two-dimensional plane corresponding to a floor surface to generate a two-dimensional image, clip the plurality of parts as independent regions on the two-dimensional image, and output respective circumscribed rectangles of the independent regions on the two-dimensional image.
In regards to claim 10, the prior art of record fails to teach or suggest the image processing apparatus according to claim 1, wherein the one or more processors extract a shape corresponding to a predetermined height from a bottom surface of a circumscribe cuboid in the three-dimensional shape data.
In regards to claim 12, the prior art of record fails to teach the image processing apparatus according to claim 1, wherein, in a case where the at least one object is located on a structure placed in an image capturing region, the one or more processors extract a shape corresponding to a predetermined height from a top surface of the structure in the three-dimensional shape data.
In regards to claim 14, the prior art of record fails to teach the image processing apparatus according to claim 4, wherein, based on the identifiers and the object position at a time immediately preceding an image capturing time of the extracted plurality of parts, the one or more processors assign the identifiers to the extracted plurality of parts.
In regards to claims 15-17, the claims depend on at least claim 14. Therefore, the claims 15-17 are allowable for at least the same reason as claim 14 if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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/ANDREW SHIN/Examiner, Art Unit 2612
/Said Broome/Supervisory Patent Examiner, Art Unit 2612