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AUSAI
2004
Springer
13 years 10 months ago
Enhanced Importance Sampling: Unscented Auxiliary Particle Filtering for Visual Tracking
Abstract. The particle filter has attracted considerable attention in visual tracking due to its relaxation of the linear and Gaussian restrictions in the state space model. It is...
Chunhua Shen, Anton van den Hengel, Anthony R. Dic...
ICPR
2008
IEEE
14 years 6 months ago
SVD based Kalman particle filter for robust visual tracking
Object tracking is one of the most important tasks in computer vision. The unscented particle filter algorithm has been extensively used to tackle this problem and achieved a grea...
Qingdi Wei, Weiming Hu, Xi Li, Xiaoqin Zhang, Yang...
CVPR
2008
IEEE
14 years 7 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 ...
ICIP
2005
IEEE
14 years 6 months ago
Visual tracking using sequential importance sampling with a state partition technique
Sequential importance sampling (SIS), also known as particle filtering, has drawn increasing attention recently due to its superior performance in nonlinear and non-Gaussian dynam...
Yan Zhai, Mark B. Yeary, Joseph P. Havlicek, Jean-...
ICIP
2009
IEEE
13 years 2 months ago
3D arm movement tracking using adaptive particle filter
In this paper, we present a monocular 3D arm movement tracking system using adaptive particle filter. The effective sample size (ESS) is analyzed in the adaptive particle filter t...
Feng Guo, Gang Qian