Robust visual tracking using multiple cues and improved particle filter

Guodong Tian; Hongling Wang

doi:10.1117/12.832755

30 October 2009 Robust visual tracking using multiple cues and improved particle filter

Guodong Tian, Hongling Wang

Proceedings Volume 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis; 74953E (2009) https://doi.org/10.1117/12.832755
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

A robust visual tracking method which can be used in complex environments is presented in this paper. The color cue and the shape cue are utilized to represent the target and fused together by democratic integration method. The multi-cue object representation is incorporated into the framework of particle filter which is a powerful probabilistic method for visual tracking. To each sample of the particle filter a mean shift operation is applied, which make the samples more effective such that the number of particles needed is significantly decreased. Unlike regular mean shift, in our method the number of mean shift iterations is limited according to the reliability of the color cue for two purposes. One is to prevent the particles from being misled by mean shift when the color cue is unreliable. The other is to reduce the waste of computation. Experimental results show that our method greatly improves the robustness and reduces the computational cost compared with the state-of-art methods.

Citation Download Citation

Guodong Tian and Hongling Wang "Robust visual tracking using multiple cues and improved particle filter", Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74953E (30 October 2009); https://doi.org/10.1117/12.832755

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KEYWORDS

Particle filters

Particles

Optical tracking

Reliability

Motion models

Detection and tracking algorithms

RGB color model

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