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CVPR
2003
IEEE
14 years 7 months ago
Variational Inference for Visual Tracking
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Jaco Vermaak, Neil D. Lawrence, Patrick Pér...
ICCV
2009
IEEE
1068views Computer Vision» more  ICCV 2009»
14 years 10 months ago
Illumination Aware MCMC Particle Filter for Long-Term Outdoor Multi-Object Simultaneous Tracking and Classification
This paper addresses real-time automatic visual tracking, labeling and classification of a variable number of objects such as pedestrians or/and vehicles, under timevarying illu...
Franc¸ois Bardet, Thierry Chateau, Datta Ramadasa...
CVPR
2005
IEEE
14 years 7 months ago
Multiple Object Tracking with Kernel Particle Filter
A new particle filter, Kernel Particle Filter (KPF), is proposed for visual tracking for multiple objects in image sequences. The KPF invokes kernels to form a continuous estimate...
Cheng Chang, Rashid Ansari, Ashfaq A. Khokhar
CVPR
2009
IEEE
2305views Computer Vision» more  CVPR 2009»
15 years 1 months ago
Visual tracking on the affine group via geometric particle filtering using optimal importance function
We propose a geometric method for visual tracking, in which the 2-D affine motion of a given object template is estimated in a video sequence by means of coordinateinvariant partic...
Junghyun Kwon (Seoul National University), Kyoung ...
ICRA
2009
IEEE
175views Robotics» more  ICRA 2009»
13 years 3 months ago
A combination of particle filtering and deterministic approaches for multiple kernel tracking
Color-based tracking methods have proved to be efficient for their robustness qualities. The drawback of such global representation of an object is the lack of information on its s...
Céline Teuliere, Éric Marchand, Laur...