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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 9/11/2025 and 3/13/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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) 1-12 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Sinha et al. (US 11302161 B1; cited by Applicant IDS).
Regarding claim 1, Sinha discloses (Figs. 5 & 9) a monitoring and tracking checkout activity in a retail environment comprising:
recognizing a product from a captured image (col. 9, lines 5-27 - detect/recognize objects of certain classes within each video frame) of a front region of a self-checkout terminal including a scanner (col. 7, line 38 – col. 8, line 11); and
detecting a fraudulent action related to a scanning operation for causing the scanner to scan product information attached to the product, based on a movement path of the product in a plurality of image areas set in the captured image (col. 10, lines 1-49), and a residence time of the product in a first image area that is closest to the scanner among the plurality of image areas (col. 11, lines 13-28 - the scan was registered within some threshold time of detecting the item).
Regarding claim 2, Sinha discloses the product of claim 1 above and further discloses wherein the plurality of image areas includes a second image area and a third image area that are disposed facing each other across the first image area, and the detecting of the fraudulent action includes determining that the fraudulent action has occurred when the product moves from the second image area to the third image area via the first image area (col. 10, lines 13-17), and the residence time of the product in the first image area is shorter than a predetermined threshold (col. 11, line 22-24).
Regarding claim 3, Sinha discloses the product of claim 2 above and further discloses wherein: the captured image is an image of the front region of the self-checkout terminal taken from above (col. 10, lines 13-17).
Regarding claim 4, Sinha discloses the product of claim 1 above and further discloses wherein: the detecting of the fraudulent action includes performing the detecting based on the movement path and the residence time each time a recognition from the captured image is made that a same person has held each of a plurality of individual products included in the product (col. 10, lines 1-49; col. 16, lines 45-49: hands of a person), and the process further includes: notifying that the fraudulent action has been detected when a number of times the fraudulent action is detected reaches a predetermined value (col. 10, lines 32-49).
Regarding claim 5, Sinha discloses the product of claim 1 above and further discloses wherein the process further includes: determining, each time a recognition from the captured image is made that a same person has held each of a plurality of individual products included in the product, for the recognized product (col. 10, lines 1-49; col. 16, lines 45-49: hands of a person), whether a first condition based on the movement path and the residence time is satisfied (col. 11, line 22-24), and whether a second condition based on the movement path is satisfied (col. 10, lines 1-49); incrementing a first count value when the first condition is satisfied (col. 18, lines 27-44), and incrementing a second count value when the second condition is satisfied (col. 10, lines 1-49; n.b. a count of at least one is inherent); and notifying that the fraudulent action has been detected when a calculation result obtained by performing weighted addition of the first count value and the second count value using a predetermined weighting coefficient reaches a predetermined value (col. 10, lines 1-49; n.b. when at least one fraudulent action is counted, the ratio of first count to second count changes from undefined to a positive number).
Regarding claim 6, Sinha discloses the product of claim 5 above and further discloses wherein: the first condition indicates that all of the plurality of image areas is passed through in a predetermined order (col. 10, lines 13-17) and that the residence time in the first image area is shorter than a predetermined threshold (col. 11, line 22-24), and the second condition indicates that, without passing through the first image area, another predetermined image area among the plurality of image areas is passed through (col. 10, lines 32-49).
Regarding claim 7, Sinha discloses the product of claim 1 above and further discloses wherein: the detecting of the fraudulent action includes detecting the fraudulent action based on the movement path, the residence time, and a characteristic of a shape of a movement trajectory of the product in the first image area (col. 10, lines 1-49: n.b. the shape characteristic is one which avoids scan; col. 11, line 22-24).
Regarding claim 8, Sinha discloses the product of claim 7 above and further discloses wherein:
the detecting of the fraudulent action includes determining the characteristic of the shape of the movement trajectory based on an entry position of the product into the first image area, a closest position of the product to the scanner in the first image area, and an exit position of the product from the first image area (col. 10, lines 1-23: analyzing changes in the intensity of image pixels across successive video frames (and/or outputs of the CNN 140 that indicate object locations across successive video frames)).
Regarding claim 9, Sinha discloses the product of claim 1 above and further discloses wherein: the detecting of the fraudulent action includes: detecting a first fraudulent action related to the scanning operation based on the movement path (col. 10, lines 1-49) and the residence time (col. 11, line 22-24), and detecting a second fraudulent action related to the scanning operation based on a recognition result of the product in the captured image (col. 9, lines 28-44) and on information regarding the product or the scanning operation of the product, the information being acquired from the self-checkout terminal (col. 7, lines 15-37), and the process further includes: executing a notification process of fraudulent action detection in a different manner depending on whether the first fraudulent action or the second fraudulent action has been detected (col. 15, lines 51-62).
Regarding claim 10, Sinha discloses the product of claim 1 above and further discloses wherein the process further includes: receiving, from the self-checkout terminal, a notification indicating that a checkout start operation has been performed on the self-checkout terminal to terminate the scanning operation and initiate checkout; and executing a notification process of fraudulent action detection in a different manner depending on whether the fraudulent action has been detected before or after the checkout start operation has been performed (Fig. 9; col. 15, lines 51-62).
Regarding claim 11, Sinha discloses:
a memory (col. 5, lines 30-42) configured to store area information indicating positions of a plurality of image areas set in a captured image of a front region of a self-checkout terminal including a scanner (col. 6, lines 58-67; col. 10, lines 1-23); and
a processor coupled to the memory and the processor (col. 4, lines 50-59) configured to:
recognize a product from the captured image (col. 9, lines 5-27 - detect/recognize objects of certain classes within each video frame), and
detect a fraudulent action related to a scanning operation for causing the scanner to scan product information attached to the product, based on a movement path of the product in the plurality of image areas (col. 10, lines 1-49), and a residence time of the product in a first image area that is closest to the scanner among the plurality of image areas (col. 11, lines 13-28 - the scan was registered within some threshold time of detecting the item).
Regarding claim 12, Sinha discloses:
a camera (col. 12, lines 20-22) configured to capture an image of a front region of a self-checkout terminal including a scanner (col. 7, line 64 – col. 8, line 11); and
a fraud detection apparatus configured to:
recognize a product from the captured image (col. 9, lines 5-27 - detect/recognize objects of certain classes within each video frame), and
detect a fraudulent action related to a scanning operation for causing the scanner to scan product information attached to the product, based on a movement path of the product in a plurality of image areas set in the captured image (col. 10, lines 1-49), and a residence time of the product in a first image area that is closest to the scanner among the plurality of image areas (col. 11, lines 13-28 - the scan was registered within some threshold time of detecting the item).
Conclusion
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/TOAN C LY/ Primary Examiner, Art Unit 2876
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