Abstract
To track a human body and estimate its posture, a component-based approach is less susceptible to changes in posture and lighting. This paper proposes model-based tracking with a component-based human body model comprised of 10 components and their hierarchical link. The proposed method first divides a video frame into blobs based on color, groups the blobs to make components, and matches the components to human body parts. Instead of matching blobs individually, the proposed model-based tacking uses components and their links. This paper shows the making of coarse-to-fine searches, so it offers a model that can make human-body matching more time-efficient.
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© 2006 Springer-Verlag Berlin Heidelberg
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Lee, KM. (2006). Component-Based Human Body Tracking for Posture Estimation. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing in Signal Processing and Pattern Recognition. Lecture Notes in Control and Information Sciences, vol 345. Springer, Berlin, Heidelberg . https://doi.org/10.1007/978-3-540-37258-5_19
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DOI: https://doi.org/10.1007/978-3-540-37258-5_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37257-8
Online ISBN: 978-3-540-37258-5
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