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Optical Engineering

Data fusion for three-dimensional tracking using particle techniques
Author(s): Huiying Chen; Youfu Li
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Paper Abstract

Robustness and tracking speed are two important indices for evaluating the performance of real-time 3-D tracking. We propose a new approach to fuse sensing data of the most current observation into a 3-D visual tracker with particle techniques. With the proposed data fusion method, the importance density function in the particle filter can be designed to represent posterior states by particle crowds in a better way. This makes the tracking system more robust to noise and outliers. On the other hand, because 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 performance of the system. Simulation and experimental results verified the effectiveness of the proposed method.

Paper Details

Date Published: 1 January 2008
PDF: 9 pages
Opt. Eng. 47(1) 016401 doi: 10.1117/1.2835013
Published in: Optical Engineering Volume 47, Issue 1
Show Author Affiliations
Huiying Chen, City Univ. of Hong Kong (Hong Kong China)
Youfu Li, City Univ. of Hong Kong (Hong Kong China)

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