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Proceedings Paper

Video-CRM: understanding customer behaviors in stores
Author(s): Ismail Haritaoglu; Myron Flickner; David Beymer
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Paper 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.

Paper Details

Date Published: 19 March 2013
PDF: 6 pages
Proc. SPIE 8663, Video Surveillance and Transportation Imaging Applications, 86630Y (19 March 2013); doi: 10.1117/12.2007327
Show Author Affiliations
Ismail Haritaoglu, Polar Rain, Inc. (United States)
Myron Flickner, IBM Almaden Research Ctr. (United States)
David Beymer, IBM Almaden Research Ctr. (United States)


Published in SPIE Proceedings Vol. 8663:
Video Surveillance and Transportation Imaging Applications
Robert Paul Loce; Eli Saber, Editor(s)

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