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» Modeling and Learning Contact Dynamics in Human Motion
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CVPR
2010
IEEE
14 years 4 months ago
Dynamical Binary Latent Variable Models for 3D Human Pose Tracking
We introduce a new class of probabilistic latent variable model called the Implicit Mixture of Conditional Restricted Boltzmann Machines (imCRBM) for use in human pose tracking. K...
Graham Taylor, Leonid Sigal, David Fleet, Geoffrey...
AR
2011
13 years 2 months ago
Learning, Generation and Recognition of Motions by Reference-Point-Dependent Probabilistic Models
This paper presents a novel method for learning object manipulation such as rotating an object or placing one object on another. In this method, motions are learned using referenc...
Komei Sugiura, Naoto Iwahashi, Hideki Kashioka, Sa...
ICARCV
2006
IEEE
420views Robotics» more  ICARCV 2006»
14 years 1 months ago
Recognizing People's Faces: from Human to Machine Vision
— As confirmed by recent neurophysiological studies, the use of dynamic information is extremely important for humans in visual perception of biological forms and motion. Apart ...
Massimo Tistarelli, Manuele Bicego, Enrico Grosso
ICCV
1999
IEEE
14 years 9 months ago
Classification of Human Body Motion
The classification of human body motion is a difficult problem. In particular, the automatic segmentation of sequences containing more than one class of motion is challenging. An ...
Jens Rittscher, Andrew Blake
IVC
2002
143views more  IVC 2002»
13 years 7 months ago
Towards the automatic analysis of complex human body motions
The classification of human body motion is an integral component for the automatic interpretation of video sequences. In a first part we present an effective approach that uses mi...
Jens Rittscher, Andrew Blake, Stephen J. Roberts