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Probabilistic Center Voting Method for Subsequent Object Tracking and Segmentation

By Hyo-kak Kim, Sang-hee Park, Dae-hwan Kim, Sung-jea Ko and Senior Member

Abstract

Abstract—In this paper, we introduce a novel algorithm for object tracking in video sequence. In order to represent the object to be tracked, we propose a spatial color histogram model which encodes both the color distribution and spatial information. The object tracking from frame to frame is accomplished via center voting and back projection method. The center voting method has every pixel in the new frame to cast a vote on whereabouts the object center is. The back projection method segments the object from the background. The segmented foreground provides information on object size and orientation, omitting the need to estimate them separately. We do not put any assumption on camera motion; the proposed algorithm works equally well for object tracking in both static and moving camera videos. Keywords—center voting, back projection, object tracking, size adaptation, non-stationary camera tracking. I

Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.352.8823
Provided by: CiteSeerX
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