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» Object tracking: A survey
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CVPR
2004
IEEE
14 years 11 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
CVPR
2007
IEEE
14 years 11 months ago
Robust Occlusion Handling in Object Tracking
In object tracking, occlusions significantly undermine the performance of tracking algorithms. Unlike the existing methods that solely depend on the observed target appearance to ...
Jiyan Pan, Bo Hu
ICIP
2007
IEEE
14 years 10 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
ICCV
2009
IEEE
3167views Computer Vision» more  ICCV 2009»
15 years 2 months ago
Tracking a Hand Manipulating an Object
We present a method for tracking a hand while it is interacting with an object. This setting is arguably the one where hand-tracking has most practical relevance, but poses signi...
Henning Hamer, Konrad Schindler, Esther Koller-Mei...
MVA
2008
125views Computer Vision» more  MVA 2008»
13 years 9 months ago
Pearson-based mixture model for color object tracking
To track objects in video sequences, many studies have been done to characterize the target with respect to its color distribution. Most often, the Gaussian Mixture Model (GMM) is ...
William Ketchantang, Stéphane Derrode, Lion...