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We present a real-time method for estimating the pose of a human body using its 3D volume obtained from synchronized videos. The method achieves pose estimation by pose regression from its 3D volume. While the 3D volume allows us to estimate the pose robustly against self occlusions, 3D volume analysis requires a large amount of computational cost. We propose fast and stable volume tracking with efficient volume representation in a low dimensional dynamical model. Experimental resultsdoi:10.1109/icpr.2010.457 dblp:conf/icpr/HiraiUK10 fatcat:ezrpalkqhrghhk3j754akdw574