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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-...
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...
ICIC
2005
Springer
13 years 10 months ago
Sequential Stratified Sampling Belief Propagation for Multiple Targets Tracking
Rather than the difficulties of highly non-linear and non-Gaussian observation process and the state distribution in single target tracking, the presence of a large, varying number...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
CAEPIA
2003
Springer
13 years 10 months ago
A Method to Adaptively Propagate the Set of Samples Used by Particle Filters
Abstract. In recent years, particle filters have emerged as a useful tool that enables the application of Bayesian reasoning to problems requiring dynamic state estimation. The ef...
Alvaro Soto
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 ...