Abstract
This paper deals with human body pose recovery through a multicamera system, which is a key task in monitoring of human activity. The proposed algorithm reconstructs the 3D visual hull of the observed body and characterizes its shape with a new 3D shape descriptor. The body pose is then infered through an original two-stage regression process. As the learning step is independant of the camera configuration, the resulting system is easy to set up. This solution is evaluated on synthetic scenes and promising results on real images are also presented.
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© 2008 Springer-Verlag Berlin Heidelberg
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Gond, L., Sayd, P., Chateau, T., Dhome, M. (2008). A 3D Shape Descriptor for Human Pose Recovery. In: Perales, F.J., Fisher, R.B. (eds) Articulated Motion and Deformable Objects. AMDO 2008. Lecture Notes in Computer Science, vol 5098. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70517-8_36
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DOI: https://doi.org/10.1007/978-3-540-70517-8_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70516-1
Online ISBN: 978-3-540-70517-8
eBook Packages: Computer ScienceComputer Science (R0)