A system and method for contextually aware customer item entry for autonomous shopping applications that includes an environmental sensing system distributed through a shopping environment that is configured to collect contextual data of customer activity in the environment; the environmental sensing system comprising at least a computer vision monitoring system, the computer vision monitoring system comprising a set of imaging devices distributed through the environment; a customer-managed item entry system that is movable through the environment by the customer and that is configured to collect item selection input; a virtual cart management module configured to manage a virtual cart with the item selection input and augmented at least in part by the contextual data, wherein the virtual cart is used in execution of an autonomous checkout process.

A system and method for contextually aware customer item entry for autonomous shopping applications that includes an environmental sensing system distributed through a shopping environment that is configured to collect contextual data of customer activity in the environment; the environmental sensing system comprising at least a computer vision monitoring system, the computer vision monitoring system comprising a set of imaging devices distributed through the environment; a customer-managed item entry system that is movable through the environment by the customer and that is configured to collect item selection input; a virtual cart management module configured to manage a virtual cart with the item selection input and augmented at least in part by the contextual data, wherein the virtual cart is used in execution of an autonomous checkout process.

An interactive shopping system, or smart cart. The system allows a user to select items in a store and complete a purchase without having to wait in lines or interact with store personnel. The system can have a container for holding products selected by at least one user, a user interface, a scanner in communication with the user interface, a processor in communication with the user interface, and a data storage comprising computer instructions executable by the processor. A user can select products, place them within the container, scan the products, and initiate a payment transaction to complete a purchase.

A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Disclosed herein are systems and methods for determining whether an unknown product matches a scanned barcode during a checkout process. An edge computing device or other computer system can receive, from an overhead camera at a checkout lane, image data of an unknown product that is placed on a flatbed scanning area, identify candidate product identifications for the unknown product based on applying a classification model and/or product identification models to the image data, and determine based on the candidate product identifications, whether the unknown product matches a product associated with a barcode that is scanned at a POS terminal in the checkout lane. The classification model can be used to determine n-dimensional space feature values for the unknown product and determine which product the unknown product likely matches. The product identification models can be used to determine whether the unknown product is one of the products that are modeled.

A customer behavioural system (100) in a store (10), the customer behavioural system (100) comprising a sensor arrangement (110) comprising one or more sensors (114a-c) and a behavioural analysis module (120). The behavioural analysis module (120) is configured to determine at least one behavioural feature (160) of a customer (20) based on sensor data from said one or more sensors (114a-c) and/or determine at least one motion event (160) of a customer (20) based on sensor data from said one or more sensors (114a-c), and determine behavioural information (122) for said customer (20) based at least on one determined behavioural feature (140) and/or at least one determined motion event (160).

A store management system includes a first determination unit, a monitoring unit, a settlement unit, a second determination unit, and a generation unit. The first determination unit determines a customer entering a store displaying and selling a commodity. The monitoring unit monitors that the customer determined by the first determination unit carries the commodity. The settlement unit settles price of the commodity monitored by the monitoring unit as being carried by the customer, according to instruction from the customer. The second determination unit determines that the customer leaves the store. The generation unit generates history data including suspicious data indicating that the customer, identified by an identification code, is associated with an unsettled commodity being carried out of the store, when a settlement of the commodity carried by the customer which is determined by the second determination unit as leaving the store has not been completed by the settlement unit.

A system and method for interaction monitoring in a retail environment that includes executing a first monitoring system and thereby generating a first evaluation of customer selection of items; executing a second monitoring system and thereby generating a second evaluation of customer selection of items; determining monitoring alignment between the first evaluation and the second evaluation of a first customer; and triggering an action in response to the monitoring alignment.

A system and method for interaction monitoring in a retail environment that includes executing a first monitoring system and thereby generating a first evaluation of customer selection of items; executing a second monitoring system and thereby generating a second evaluation of customer selection of items; determining monitoring alignment between the first evaluation and the second evaluation of a first customer; and triggering an action in response to the monitoring alignment.

Embodiments of the present invention provide a skip-scanning identification method and apparatus, a self-service cash register terminal and system. The method includes: obtaining a video of a user scanning an item; determining posture data of the user based on the obtained video; determining, according to the posture data of the user, a time period in which a scanning action of the user takes place; receiving a scanning result of the item; and determining whether the user has skipped scanning the item based on the scanning result and the time period.