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CVPR
2005
IEEE
14 years 8 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
PAMI
2008
235views more  PAMI 2008»
13 years 5 months ago
Dependent Multiple Cue Integration for Robust Tracking
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and po...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
ICCV
2005
IEEE
14 years 8 months ago
Integration of Conditionally Dependent Object Features for Robust Figure/Background Segmentation
We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and p...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
PAMI
2007
191views more  PAMI 2007»
13 years 5 months ago
Adaptive Object Tracking Based on an Effective Appearance Filter
We propose a similarity measure based on a Spatial-color Mixture of Gaussians (SMOG) appearance model for particle filters. This improves on the popular similarity measure based o...
Hanzi Wang, David Suter, Konrad Schindler, Chunhua...
ICIP
2007
IEEE
14 years 8 months ago
MAP Particle Selection in Shape-Based Object Tracking
The Bayesian filtering for recursive state estimation and the shape-based matching methods are two of the most commonly used approaches for target tracking. The Multiple Hypothesi...
Alessio Dore, Carlo S. Regazzoni, Mirko Musso