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» A Bayesian Framework for Multi-cue 3D Object Tracking
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NIPS
2000
13 years 8 months ago
Learning and Tracking Cyclic Human Motion
We present methods for learning and tracking human motion in video. We estimate a statistical model of typical activities from a large set of 3D periodic human motion data by segm...
Dirk Ormoneit, Hedvig Sidenbladh, Michael J. Black...
ICASSP
2009
IEEE
13 years 5 months ago
Robust Bayesian tracking on Riemannian manifolds via fragments-based representation
Recently, the covariance region descriptor [1] has been proved robust and versatile for a modest computational cost. It enables efficient fusion of different types of features. Ba...
Yi Wu, Jinqiao Wang, Hanqing Lu
ICCV
2009
IEEE
13 years 5 months ago
Tracking a large number of objects from multiple views
We propose a multi-object multi-camera framework for tracking large numbers of tightly-spaced objects that rapidly move in three dimensions. We formulate the problem of finding co...
Zheng Wu, Nickolay I. Hristov, Tyson L. Hedrick, T...
CVPR
2008
IEEE
14 years 9 months ago
Multi-object shape estimation and tracking from silhouette cues
This paper deals with the 3D shape estimation from silhouette cues of multiple moving objects in general indoor or outdoor 3D scenes with potential static obstacles, using multipl...
Li Guan, Jean-Sébastien Franco, Marc Pollef...
CVPR
2005
IEEE
14 years 9 months ago
Kernel-Based Bayesian Filtering for Object Tracking
Particle filtering provides a general framework for propagating probability density functions in non-linear and non-Gaussian systems. However, the algorithm is based on a Monte Ca...
Bohyung Han, Ying Zhu, Dorin Comaniciu, Larry S. D...