Monitoring system capable of classifying items added to a shopping cart

US11208134B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11208134-B2
Application numberUS-202117196843-A
CountryUS
Kind codeB2
Filing dateMar 9, 2021
Priority dateMar 11, 2020
Publication dateDec 28, 2021
Grant dateDec 28, 2021

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

A system for monitoring shopping carts uses cameras to generate images of the carts moving in a store. In some implementations, cameras may additionally or alternatively be mounted to the shopping carts and configured to image cart contents. The system may use the collected image data, and/or other types of sensor data (such as the store location at which an item was added to the basket), to classify items detected in the shopping carts. For example, a trained machine learning model may classify item in a cart as “non-merchandise,” “high theft risk merchandise,” “electronics merchandise,” etc. When a shopping cart approaches a store exit without any indication of an associated payment transaction, the system may use the associated item classification data, optionally in combination with other data such as cart path data, to determine whether to execute an anti-theft action, such as locking a cart wheel or activating a store alarm. The system may also compare the classifications of cart contents to payment transaction records (or summaries thereof) to, e.g., detect underpayment events.

First claim

Opening claim text (preview).

What is claimed is: 1. A system for reducing push-out theft, comprising: a camera positioned to capture images of contents of shopping carts associated with a store, wherein the shopping carts have different respective identifiers; and a computing system comprising one or more processors, the computing system programmed to implement at least: an item classifier that assigns classifications to items detected in the shopping carts based on analyses of the images using a trained machine learning model; and an exit manager that determines whether to authorize a shopping cart to exit the store based on at least (1) a classification assigned by the item classifier to at least one item in the shopping cart, and (2) indicia of whether the at least one item has been paid for; wherein the computing system is additionally programmed to determine the identifier of a shopping cart imaged by said camera and to use the determined identifier to send a shopping-cart-specific command to the imaged shopping cart, said command based on an exit authorization determination made by the exit manager. 2. The system of claim 1 , wherein the camera is mounted in a fixed location in the store. 3. The system of claim 2 , wherein the imaged shopping cart comprises at least one wheel assembly that senses, and reports on a wireless network, wheel rotation events, and wherein the computing system is programmed to use the wheel rotation events to match the identifier of the imaged shopping cart to a cart track detected in a sequences of images captured by the camera. 4. The system of claim 1 , wherein the camera is mounted to the shopping cart. 5. The system of claim 4 , wherein the camera is part of a cart-mounted camera module that includes a processor configured to assess whether an item has been added to the shopping cart by comparing a first image captured by the camera to a second, subsequent image captured by the camera. 6. The system of claim 5 , wherein the camera module further comprises a wireless transceiver, and the processor is configured to use the wireless transceiver to upload the second image on a wireless network for analysis in response to detecting a possible addition of an item to the shopping cart. 7. The system of claim 1 , wherein the item classifier is configured to classify items detected in a shopping cart as merchandise versus non-merchandise items. 8. The system of claim 1 , wherein the item classifier is configured to assign merchandise category classifications to items detected in a shopping cart. 9. The system of claim 1 , wherein the item classifier is configured to classify an item added to the shopping cart based at least partly on a store location of the shopping cart at a time the item is added. 10. The system of claim 1 , wherein the computing system is further programmed to: identify, based on a monitored location of the shopping cart, a payment point potentially used to pay for merchandise in the shopping cart; and compare a record of a transaction executed by the pay point to item classifications assigned by the item classifier to items detected in the shopping cart. 11. The system of claim 10 , wherein the computing system is further configured to detect, based on the comparison, an underpayment event in which a customer pays for less than all items in the shopping cart. 12. The system of claim 10 , wherein the computing system is further configured to determine whether the shopping cart returns to a merchandise area after payment without first exiting the store. 13. The system of claim 1 , wherein the camera has a wavelength response that encompasses near IR and/or near UV. 14. A process for reducing push-out theft, comprising: monitoring a location of a shopping cart in a store, said shopping cart being one of a plurality of shopping carts that are associated with the store, said shopping carts having different respective identifiers; detecting an event in which an item is added to the shopping cart; assigning a classification to the item based on at least one of the following: (1) a location of the shopping cart in the store at a time of the event, as determined from said monitoring, and (2) an image captured by a camera of the item in the shopping cart; determining the identifier of the shopping cart; subsequently, detecting that the shopping cart is exiting the store without indicia of an associated payment transaction; in response to determining that the shopping cart is exiting, determining, based at least partly on the classification assigned to the item, whether to perform an anti-theft action; and transmitting a shopping-cart-specific message to the shopping cart using the determined identifier, said message based on the determination of whether to perform an anti-theft action; said process performed under control of program instructions executed by one or more processors. 15. The process of claim 14 , wherein detecting said event comprises detecting, with a vibration sensor mounted to the shopping cart, vibration caused by the item being added to the shopping cart. 16. The process of claim 14 , wherein the shopping cart comprises a camera module having a camera and a processor, and wherein detecting said event comprises, by the camera module, comparing a first image captured by the camera to a second, subsequent image captured by the camera to determine whether contents of the shopping cart have changed. 17. The process of claim 16 , wherein the camera module further comprises a wireless transceiver, and the process further comprises, by the camera module, uploading the second image, or a representation of the second image, on a wireless network for analysis in response to detecting a change to basket contents. 18. The process of claim 14 , wherein assigning a classification to the item comprises using a trained machine learning model to classify the item as merchandise versus non-merchandise. 19. The process of claim 14 , wherein assigning a classification to the item comprises determining a merchandise identifier of the item. 20. The process of claim 14 , wherein assigning a classification to the item comprises assigning a merchandise category to the item. 21. The process of claim 14 , wherein the classification is assigned based at least partly on an image captured by a camera of the item in the basket of the shopping cart. 22. The process of claim 14 , wherein the camera is mounted in a fixed location in the store. 23. The process of claim 22 , wherein the shopping cart comprises a wheel assembly that senses, and reports on a wireless network, wheel rotation events, and wherein the process further comprises using the reported wheel rotation events to match the identifier of the shopping cart to a cart track detected in a sequence of images captured by the camera. 24. The process of claim 14 , wherein the camera is mounted to a basket of the shopping cart. 25. The process of claim 14 , wherein the classification is assigned based at least partly on a location of the shopping cart in the store at a time of the event. 26. The process of claim 14 , further comprising: identifying, based on the monitored location of the shopping cart, a payment point potentially used to pay for merchandise in the shopping cart; and comparing a record of a transaction executed by the pay point to item classifications assigned to one or more items detected in the basket of the shoppin

Assignees

Inventors

Classifications

  • G07G3/003Primary

    Anti-theft control (theft alarms G08B13/00) · CPC title

  • B62B5/0423Primary

    braking or blocking when leaving a particular area · CPC title

  • using neural networks · CPC title

  • Generating training patterns; Bootstrap methods, e.g. bagging or boosting · CPC title

  • Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound · CPC title

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Frequently asked questions

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What does patent US11208134B2 cover?
A system for monitoring shopping carts uses cameras to generate images of the carts moving in a store. In some implementations, cameras may additionally or alternatively be mounted to the shopping carts and configured to image cart contents. The system may use the collected image data, and/or other types of sensor data (such as the store location at which an item was added to the basket), to cl…
Who is the assignee on this patent?
Gatekeeper Systems Inc
What technology area does this patent fall under?
Primary CPC classification G07G3/003. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Dec 28 2021 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 12 related publications on this page (citations in our corpus or others sharing the same primary CPC).