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Markerless and Efficient 26-DOF Hand Pose Recovery

Summary: Markerless and Efficient 26-DOF
Hand Pose Recovery
Iasonas Oikonomidis, Nikolaos Kyriazis, and Antonis A. Argyros
Institute of Computer Science, FORTH
Computer Science Department, University of Crete
{oikonom|kyriazis|argyros}@ics.forth.gr http://www.ics.forth.gr/cvrl/
Abstract. We present a novel method that, given a sequence of syn-
chronized views of a human hand, recovers its 3D position, orientation
and full articulation parameters. The adopted hand model is based on
properly selected and assembled 3D geometric primitives. Hypothesized
configurations/poses of the hand model are projected to different cam-
era views and image features such as edge maps and hand silhouettes are
computed. An objective function is then used to quantify the discrepancy
between the predicted and the actual, observed features. The recovery of
the 3D hand pose amounts to estimating the parameters that minimize
this objective function which is performed using Particle Swarm Opti-
mization. All the basic components of the method (feature extraction,
objective function evaluation, optimization process) are inherently paral-
lel. Thus, a GPU-based implementation achieves a speedup of two orders


Source: Argyros, Antonis - Foundation of Research and Technology, Hellas & Department of Computer Science, University of Crete


Collections: Computer Technologies and Information Sciences