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 .
Status of the Claims
Claims 1-20 are presented for Examination. Applicant filed a response to non-final Office action on 10/17/2025 amending claims 1-20. In light of Applicant’s amendments, Examiner has withdrawn previous objection of dependent claims 2-10 and 12-19; and previous § 101 and § 102 rejections for claims 1-20. Examiner has, however, established a new objection for claim 11 and new § 112(b) rejection for claims 1-20 in the instant Office action. Since the new § 112(b) rejection was necessitated by Applicant’s amendments, the instant rejection of claims 1-20 is FINAL rejection of the claims.
Examiner’s Remarks
Patent Eligibility under § 101: Newly amended independent claims 1, 11, and 20, integrate the recited abstract idea into practical application based on the following limitations:
a scanner configured to scan an identifier on a first item;
a camera configured to capture a first image of the first item as the scanner is scanning the identifier on the first item;
a memory; and
one or more processors communicatively coupled to the memory, a combination of the one or more processors configured to:
obtain a scanned identity of the first item based, at least in part, on the scanner scanning the identifier on the first item;
extract information about the first item from the first image of the first item;
determine a mismatch between the scanned identity of the first item and the predicted identity of the first item;
generate an alert indicating the mismatch between the scanned identity of the first item and the predicted identity of the first item; and
display the alert on a display device for viewing by one or more persons.
Prior Art under § 102 and § 103:
Closest identified prior art reference Krishnamurthy (US 2024/0020859 A1) teaches:
In response to detecting a first triggering event corresponding to placement of a first item on a platform, a plurality of first images are captured of the first item. An item identifier associated with the first item is identified based on the first images and assigned to the first item. In response to detecting a second triggering event corresponding to placement of a second item on the platform, a plurality of second images are captured of the second item, a plurality of cropped images are generated based on the second images, and a plurality of item identifiers are determined for the second item based on the cropped images. When a process for selecting a particular item identifier from the plurality of item identifiers fails, a second item identifier is assigned to the second item based on an association between the first item identifier and the second item identifier.
Another prior art reference Rodriguez (US 2021/0304173 A1) discloses:
A computing device is associated with a retail store. As a customer scans his/her items for purchase, images of a bag containing the items are captured and sent to the computing device to be digitally processed. Based on the processing, the computing device identifies the item(s) the customer intends to purchase, and determines whether there are any other items in the container that are different from the first item. If so, the computing device outputs a signal indicating the presence of the second item in the container.
Neither Krishnamurthy, nor Rodriguez, discloses the following claim limitations – alone or in combination with each other or other references – found in independent claims 1, 11, and 20, as an ordered combination of steps with other claim steps:
a scanner configured to scan an identifier on a first item;
a camera configured to capture a first image of the first item as the scanner is scanning the identifier on the first item;
a memory; and
one or more processors communicatively coupled to the memory, a combination of the one or more processors configured to:
obtain a scanned identity of the first item based, at least in part, on the scanner scanning the identifier on the first item;
extract information about the first item from the first image of the first item;
determine a mismatch between the scanned identity of the first item and the predicted identity of the first item;
generate an alert indicating the mismatch between the scanned identity of the first item and the predicted identity of the first item; and
display the alert on a display device for viewing by one or more persons.
Claim Objections
Claims 11 is objected to because of the following informality: there should be one or more processors performing the recited claim steps.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. § 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-20 are rejected under 35 U.S.C. § 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 1 recites:
in response to determining that both the first probability and the second probability are below a threshold, determine, based on a shopping history of a user purchasing the first item, that the user previously purchased a second item comprising a characteristic;
Claim 11 recites:
in response to determining that both the first probability and the second probability are below a threshold, determining, based on a shopping history of a user purchasing the first item, that a user purchasing the first item previously purchased a second item comprising a characteristic;
Claim 20 recites:
determine, based on a shopping history of a user purchasing the item, a weight;
It is not clear whether “a user” the one and the same user in each case, or whether there is two different users – in which case the second user should be called, e.g., “another user.” Therefore independent claims 1, 11, and 17, are rejected under § 112(b) as indefinite, and dependent claims 2-10 and 11-19 are rejected under § 112(b) based on their dependency.
(1) If the users are different, Applicant could amend the claims 1, 11, and 20 to recite:
Claim 1:
in response to determining that both the first probability and the second probability are below a threshold, determine, based on a shopping history of a user purchasing the first item, that [[the]] another user previously purchased a second item comprising a characteristic;
Claim 11:
in response to determining that both the first probability and the second probability are below a threshold, determining, based on a shopping history of a user purchasing the first item, that [[a]] another user purchasing the first item previously purchased a second item comprising a characteristic;
Claim 20:
determine, based on a shopping history of a user purchasing the item, a weight based on a shopping history of another user;
and
(2) If the users are the same, Applicant could amend the claim 11 to recite:
Claim 11:
in response to determining that both the first probability and the second probability are below a threshold, determining, based on a shopping history of a user purchasing the first item, that [[a]] the user purchasing the first item previously purchased a second item comprising a characteristic;
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Huang (US 12,205,098 B2) discloses: “A smart shopping cart includes internally facing cameras and an integrated scale to identify objects that are placed in the cart. To avoid unnecessary processing of images that are irrelevant, and thereby save battery life, the cart uses the scale to detect when an object is placed in the cart. The cart obtains images from a cache and sends those to an object detection machine learning model. The cart captures and sends a load curve as input to the trained model for object detection. Labeled load data and labeled image data are used by a model training system to train the machine learning model to identify an item when it is added to the shopping cart. The shopping cart also uses weight data and the image data from a timeframe associated with the addition of the item to the cart as inputs.”
Zucker (US 10,984,239 B2) discloses: “Various embodiments herein each include at least one of systems, methods, software, and data structures for context-aided machine vision. For example, one method embodiment includes identifying a customer in a shopping area and maintaining an item bin in a computing system of data identifying items the customer has picked up for purchase. This method further includes receiving an image of the customer holding an item and performing item identification processing on the image to identify the item the customer is holding. The item identification processing may be performed based in part on a stored shopping history of the customer indicating items the customer is more likely to purchase. The identified item is then added to the item bin of the customer.”
Gokturk (US 8,898,169 B2) discloses: “Product data for a product is received by an attribute selection module. The product data includes product image data and product text data. This product data is used to generate a plurality of probability distributions for a category. The category includes a plurality of attributes, and the probability distribution includes a plurality of probabilities indicating the likelihoods that attributes of the category are applicable to the product. The plurality of probability distributions for the category are weighted and summed to generate a combined probability distribution for the category. An attribute label is determined by selecting an attribute from the category that is indicated to be most likely applicable to the product based on the combined probability distribution for the category. The attribute label is associated with the product. The attribute label enables other services to search for and retrieve the product based on the attribute.”
Morimura (US 2018/0300643 A1) discloses: “Similarity of items can be estimated by using a method including generating a prediction model that predicts an indicator of a target based on one or more attributes for items, by estimating a weight set, among weight sets, for each of the items, and estimating a similarity among the items for the target based on the weight sets of the prediction model.”
Tung (US 2007/0124110 A1) discloses: “The method involves extracting a set of features of several objects on a web page. A probability of each of the object which is a primary product object is computed based on the set of features e.g. statistical model. The primary product object is selected based on the probabilities. The set of features is selected from the group consisting of geometric features, stylistic features, file features, file hosting features, and alternative text features.”
Applicant's amendment necessitated the new grounds 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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VIRPI H. KANERVO whose telephone number is 571-272-9818. The examiner can normally be reached on Monday – Friday, 10 am – 6 pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor Abhishek Vyas can be reached on 571-270-1836. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/VIRPI H KANERVO/Primary Examiner, Art Unit 3691