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» Gibbs Likelihoods for Bayesian Tracking
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PREMI
2007
Springer
14 years 11 days ago
An Adaptive Bayesian Technique for Tracking Multiple Objects
Abstract. Robust tracking of objects in video is a key challenge in computer vision with applications in automated surveillance, video indexing, human-computer-interaction, gesture...
Pankaj Kumar, Michael J. Brooks, Anton van den Hen...
ICCV
2007
IEEE
13 years 8 months ago
Probabilistic Fusion Tracking Using Mixture Kernel-Based Bayesian Filtering
Even though sensor fusion techniques based on particle filters have been applied to object tracking, their implementations have been limited to combining measurements from multip...
Bohyung Han, Seong-Wook Joo, Larry S. Davis
CVPR
2005
IEEE
14 years 8 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...
ICCV
2011
IEEE
12 years 6 months ago
Real-time Indoor Scene Understanding using Bayesian Filtering with Motion Cues
We present a method whereby an embodied agent using visual perception can efficiently create a model of a local indoor environment from its experience of moving within it. Our me...
Grace Tsai, Changhai Xu, Jingen Liu, Benjamin Kuip...
CVPR
2003
IEEE
14 years 8 months ago
Tracking Appearances with Occlusions
Occlusion is a difficult problem for appearance-based target tracking, especially when we need to track multiple targets simultaneously and maintain the target identities during t...
Ying Wu, Ting Yu, Gang Hua