Enhanced particles with pseudolikelihoods for three-dimensional tracking

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Original languageEnglish
Pages (from-to)2992-2997
Journal / PublicationIEEE Transactions on Industrial Electronics
Issue number8
Publication statusPublished - 2009


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. © 2009 IEEE.

Research Area(s)

  • 3-D tracking, Importance density, Particle filtering, Pseudolikelihood