Probabilistic Center Voting Method for Subsequent Object Tracking and Segmentation

Autor: Suryanto, Hyo-Kak Kim, Park, Sang-Hee, Dae-Hwan Kim, Sung-Jea Ko
Jazyk: angličtina
Rok vydání: 2009
Předmět:
DOI: 10.5281/zenodo.1061745
Popis: 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.
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Databáze: OpenAIRE
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