Enhanced Particles With Pseudolikelihoods for Three-Dimensional Tracking
Huiying Chen
Youfu Li
Dept. of Ind. & Syst. Eng., Hong Kong Polytech. Univ., Hong Kong, China;
This paper appears in: Industrial Electronics, IEEE Transactions on
Publication Date: Aug. 2009
Volume: 56,
Issue: 8
On page(s): 2992-2997
ISSN: 0278-0046
INSPEC Accession Number: 10793154
Digital Object Identifier: 10.1109/TIE.2009.2024099
First Published: 2009-06-02
Current Version Published: 2009-07-24
Abstract
In this paper, we propose a new method to fuse sensing data of the most current observation into a 3-D visual tracker using pseudolikelihood functions with particle filtering techniques. With the proposed approach, the importance density function in particle filter can be modified to represent posterior states by particle crowds in a better way. Thus, it makes the tracking system more robust to noise and outliers. On the other hand, because the particle interpretation is performed in a much more efficient fashion, the number of particles used in tracking is greatly reduced, which improves the real-time performances of the system. Simulation and experimental results verified the effectiveness of the proposed method.
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