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ICCV
2003
IEEE
14 years 9 months ago
Tracking Articulated Body by Dynamic Markov Network
A new method for visual tracking of articulated objects is presented. Analyzing articulated motion is challenging because the dimensionality increase potentially demands tremendou...
Ying Wu, Gang Hua, Ting Yu
FGR
2000
IEEE
175views Biometrics» more  FGR 2000»
14 years 2 days ago
A Framework for Modeling the Appearance of 3D Articulated Figures
This paper describes a framework for constructing a linear subspace model of image appearance for complex articulated 3D figures such as humans and other animals. A commercial mo...
Hedvig Sidenbladh, Fernando De la Torre, Michael J...
CVPR
1997
IEEE
14 years 9 months ago
Learning Parameterized Models of Image Motion
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...
Michael J. Black, Yaser Yacoob, Allan D. Jepson, D...
CVPR
2008
IEEE
14 years 9 months ago
Drift-free tracking of rigid and articulated objects
Model-based 3D tracker estimate the position, rotation, and joint angles of a given model from video data of one or multiple cameras. They often rely on image features that are tr...
Juergen Gall, Bodo Rosenhahn, Hans-Peter Seidel
CVPR
2007
IEEE
14 years 9 months ago
Recognizing Human Activities from Silhouettes: Motion Subspace and Factorial Discriminative Graphical Model
We describe a probabilistic framework for recognizing human activities in monocular video based on simple silhouette observations in this paper. The methodology combines kernel pr...
Liang Wang, David Suter