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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Object Tracking with Self-updating Tracking Window
verfasst von : Huimin Qian, Yaobin Mao, Jason Geng, Zhiquan Wang
Erschienen in: Intelligence and Security Informatics
Verlag: Springer Berlin Heidelberg
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A basic requirement for a practical tracking system is to adjust the tracking model in real time when the appearance of the tracked object changes. However, since the scale of the targets often varied irregularly, systems with fixed-size tracking window usually could not accommodate to these scenarios. In present paper, a new multi-scale information measure for image was introduced to probe the size-changes of tracked objects. An automatic window-size updating method was then proposed and integrated into the classical color histogram based mean-shift and particle filtering tracking frameworks. Experimental results demonstrated that the improved algorithms could select the proper size of tracking window not only when the object scale increases but the scale decreases as well with minor extra computational overhead.