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SETN
2010
Springer
13 years 5 months ago
Visual Tracking by Adaptive Kalman Filtering and Mean Shift
A method for object tracking combining the accuracy of mean shift with the robustness to occlusion of Kalman filtering is proposed. At first, an estimation of the object's pos...
Vasileios Karavasilis, Christophoros Nikou, Aristi...
CVPR
2008
IEEE
14 years 9 months ago
Sequential particle swarm optimization for visual tracking
Visual tracking usually involves an optimization process for estimating the motion of an object from measured images in a video sequence. In this paper, a new evolutionary approac...
Xiaoqin Zhang, Weiming Hu, Stephen J. Maybank, Xi ...
CVPR
2000
IEEE
13 years 11 months ago
Adaptive Bayesian Recognition in Tracking Rigid Objects
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
Yuri Boykov, Daniel P. Huttenlocher
ICPR
2008
IEEE
14 years 8 months ago
Robust tracking of spatial related components
This paper introduces a hierarchical approach for multicomponent tracking, where the object-to-be-tracked is modeled as a group of spatial related parts. We propose to use a robus...
Horst Bischof, Michael Donoser, Thomas Mauthner
CVPR
2005
IEEE
14 years 9 months ago
Appearance-Guided Particle Filtering for Articulated Hand Tracking
We propose a model-based tracking method, called appearance-guided particle filtering (AGPF), which integrates both sequential motion transition information and appearance informa...
Wen-Yan Chang, Chu-Song Chen, Yi-Ping Hung