Abstract
To detect a human body and recognize its posture, a component-based approach is less susceptible to changes in posture and lighting conditions. This paper proposes a component-based human-body model that comprises ten components and their flexible links. Each component contains geometrical information, appearance information, and information on the links with other components. The proposed method in this paper uses hierarchical links between components of human body, so that it allows to make coarse-to-fine searches and makes human-body matching more time-efficient. To adaptively estimate the posture in change of posture and illumination, we update the component online every time a new human body is incoming.
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© 2005 Springer-Verlag Berlin Heidelberg
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Lee, KM. (2005). Adaptive Estimation of Human Posture Using a Component-Based Model. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_36
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DOI: https://doi.org/10.1007/11552499_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28833-6
Online ISBN: 978-3-540-31999-3
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