Video verification of point of sale transactions

Loss prevention is a significant challenge in retail enterprises. A significant percentage of this loss occurs at point of sale (POS) terminals. POS data mining tools known collectively as exception based reporting (EBR) are helping retailers, but they have limitations as they can only work statistically on trends and anomalies in digital POS data. By applying video analytics techniques to POS transactions, it is possible to detect fraudulent or anomalous activity at the level of individual transactions. Very specific fraudulent behaviors that cannot be detected via POS data alone become clear when combined with video-derived data. ObjectVideo, a provider of intelligent video software, has produced a system called RetailWatch that combines POS information with video data to create a unique loss prevention tool. This paper describes the system architecture, algorithmic approach, and capabilities of the system, together with a customer case-study illustrating the results and effectiveness of the system.