Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/13705
Title: New multi-step sampling with adaptive sampling patterns in particle filtering for tracking in surveillance systems
Authors: Chen, Z
Siu, WC 
Issue Date: 2013
Source: Digest of technical papers - IEEE International Conference on Consumer Electronics, 2013, 6486897, p. 286-287 How to cite?
Abstract: Particle filtering is one of the most efficient approaches for object tracking in video application systems. In this paper, we propose a new multi-step recursive sampling method to replace the conventional direct importance sampling. An online-adaptive sampling pattern for proposal distributions is established. New particles are then sampled recursively from the existing particles with high weights. A 2D predictive transition vector is used to update the pattern of the multivariate Gaussian sampling. Experimental results illustrate that the proposed method reduces computation substantially and it also preserves good tracking results comparable to other algorithms in the literature.
Description: 2013 IEEE International Conference on Consumer Electronics, ICCE 2013, Las Vegas, NV, 11-14 January 2013
URI: http://hdl.handle.net/10397/13705
ISBN: 9781467313612
ISSN: 0747-668X
DOI: 10.1109/ICCE.2013.6486897
Appears in Collections:Conference Paper

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