Skeleton and Shape Adjustment and Tracking in Multicamera Environments

Abstract

AbstractIn 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.KeywordsMotion CaptureBody ModelMotion TrackingKinematic ChainVisual HullThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.