Abstract: A system for detecting scan and non-scan events in a self-check out (SCO) process includes a a scanner for scanning objects and generating point of sale (POS) data, a video camera for generating a video of the scanning region, proximity sensors proximal to the video camera for defining an Area of Action (AoA), wherein the video camera starts capturing scanning region, when the objects enter the AoA, and the POS data includes non-zero values, an Artificial neural network (ANN) for receiving an image frame and generating one or more values, each indicating a probability of classification of the image frame into one or more classes respectively, and a processing unit for processing the POS data, and probabilities of one or more classes to detect a correlation between video data and POS data, and detect one of: scan and non-scan event in the image frame based on the correlation.

Abstract: An order checking system includes video sensors configured to capture video footage of a monitored area located in proximity to a receipt/dispatch portal. A processing unit performs event analysis on the captured video footage, detects an entity and from a door opening event, an incoming delivery from a third-party supplier, identifies the third-party supplier and implements a check-in process for delivery persons associated therewith, detects an ingress/egress of merchandise through the receipt/dispatch portal and validates that detected delivered products matches with data regarding products that the third-party supplier should be delivering. A database stores at least a dataset of face images/logos for detecting faces/brands and a dataset of product images for identification of products. The database records an outcome of an order checking process and a check out of a delivery person at an end of a delivery.

Abstract: A system for detecting scan and non-scan events in a self-check out (SCO) process includes a a scanner for scanning objects and generating point of sale (POS) data, a video camera for generating a video of the scanning region, proximity sensors proximal to the video camera for defining an Area of Action (AoA), wherein the video camera starts capturing scanning region, when the objects enter the AoA, and the POS data includes non-zero values, an Artificial neural network (ANN) for receiving an image frame and generating one or more values, each indicating a probability of classification of the image frame into one or more classes respectively, and a processing unit for processing the POS data, and probabilities of one or more classes to detect a correlation between video data and POS data, and detect one of: scan and non-scan event in the image frame based on the correlation.