About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
VSTIA 2013
Conference paper
Video-CRM: Understanding customer behaviors in stores
Abstract
This paper describes two real-time computer vision systems created 10 years ago that detect and track people in stores to obtain insights of customer behavior while shopping. The first system uses a single color camera to identify shopping groups in the checkout line. Shopping groups are identified by analyzing the inter-body distances coupled with the cashier's activities to detect checkout transactions start and end times. The second system uses multiple overhead narrow-baseline stereo cameras to detect and track people, their body posture and parts to understand customer interactions with products such as "customer picking a product from a shelf". In pilot studies both systems demonstrated real-time performance and sufficient accuracy to enable more detailed understanding of customer behavior and extract actionable real-time retail analytics. © 2013 SPIE-IS&T.