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Particle Filtering with Multiple Cues for Object Tracking in Video Sequences

Brasnett, P. and Mihaylova, L. and Canagarajah, N. and Bull, D. (2005) Particle Filtering with Multiple Cues for Object Tracking in Video Sequences. In: SPIE Proceedings. SPIE, pp. 430-441.

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Abstract

In this paper we investigate object tracking in video sequences by using the potential of particle filtering to process features from video frames. A particle filter (PF) and a Gaussian sum particle filter (GSPF) are developed based upon multiple information cues, namely colour and texture, which are described with highly nonlinear models. The algorithms rely on likelihood factorisation as a product of the likelihoods of the cues. We demonstrate the advantages of tracking with multiple independent complementary cues compared to tracking with individual cues. The advantages are increased robustness and improved accuracy. The performance of the two filters is investigated and validated over both synthetic and natural video sequences.

Item Type: Contribution in Book/Report/Proceedings
Additional Information: Publisher: SPIE
Uncontrolled Keywords: particle filtering ; Bayesian methods ; tracking in video sequences ; colour ; texture ; Gaussian sum particle filtering ; DCS-publications-id ; inproc-429 ; DCS-publications-credits ; dsp ; DCS-publications-personnel-id ; 121
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 4366
Deposited By: Dr L Mihaylov
Deposited On: 07 Mar 2008 16:18
Refereed?: No
Published?: Published
Last Modified: 17 Sep 2013 09:34
Identification Number:
URI: http://eprints.lancs.ac.uk/id/eprint/4366

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