Particle filtering with multiple cues for object tracking in video sequences

PA Brasnett, LS Mihaylova, CN Canagarajah, DR Bull

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

42 Citations (Scopus)

Abstract

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.
Translated title of the contributionParticle filtering with multiple cues for object tracking in video sequences
Original languageEnglish
Title of host publicationIS & T/SPIE 17th Annual Symposium Image and Video Communications Processing 2005, San Jose, CA, USA
PublisherSociety of Photo-Optical Instrumentation Engineers (SPIE)
Pages430 - 441
Number of pages12
Volume5685
DOIs
Publication statusPublished - 18 Jan 2005

Fingerprint Dive into the research topics of 'Particle filtering with multiple cues for object tracking in video sequences'. Together they form a unique fingerprint.

Cite this