Abstract
In this paper we present a method for automatic body model adjustment and motion tracking in multicamera environments. We introduce a set of shape deformation parameters based on linear blend skinning, that allow a deformation related to the scaling of the distinct bones of the body model skeleton, and a deformation in the radial direction of a bone. The adjustment of a generic body model to a specific subject is achieved by the estimation of those shape deformation parameters. This estimation combines a local optimization method and hierarchical particle filtering, and uses an efficient cost function based on foreground silhouettes using GPU. This estimation takes into account anthropometric constraints by using a rejection sampling method of propagation of particles. We propose a hierarchical particle filtering method for motion tracking using the adjusted model. We show accurate model adjustment and tracking for distinct subjects in a 5 cameras set up.
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Alcoverro, M., Casas, J.R., Pardàs, M. (2010). Skeleton and Shape Adjustment and Tracking in Multicamera Environments. In: Perales, F.J., Fisher, R.B. (eds) Articulated Motion and Deformable Objects. AMDO 2010. Lecture Notes in Computer Science, vol 6169. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14061-7_9
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DOI: https://doi.org/10.1007/978-3-642-14061-7_9
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