Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001 (2001)
Dec. 8, 2001 to Dec. 14, 2001
Ismail Haritaoglu , IBM Almaden Research Center
Myron Flickner , IBM Almaden Research Center
We describe a monocular real-time computer vision system that identifies shopping groups by detecting and tracking multiple people as they wait in a checkout line or service counter. Our system segments each frame into foreground regions which contains multiple people. Foreground regions are further segmented into individuals using a temporal segmentation of foreground and motion cues. Once a person is detected, an appearance model based on color and edge density in conjunction with a mean-shift tracker is used to recover the person?s trajectory. People are grouped together as a shopping group by analyzing interbody distances. The system also monitors the cashier?s activities to determine when shopping transactions start and end. Experimental results demonstrate the robustness and real-time performance of the algorithm.
M. Flickner and I. Haritaoglu, "Detection and Tracking of Shopping Groups in Stores," Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001(CVPR), Kauai, Hawaii, 2001, pp. 431.