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Erschienen in:
2014 | OriginalPaper | Buchkapitel
A Robust Integrated Framework for Segmentation and Tracking
verfasst von : Prabhu Kaliamoorthi, Ramakrishna Kakarala
Erschienen in: Image and Video Technology
Verlag: Springer Berlin Heidelberg
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Recent studies on human motion capture (HMC) indicate the need for a likelihood model that does not rely on a static background. In this paper, we present an approach to human motion capture using a robust version of the oriented chamfer matching scheme. Our method relies on an MRF based segmentation to isolate the subject from the background, and therefore does not require a static background. Furthermore, we use robust statistics and make the likelihood robust to outliers. We compare the proposed approach to the alternative methods used in recent studies in HMC using the Human Eva I dataset. We show that our method performs significantly better than the alternatives despite of not assuming a static background.