Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Huiyu Zhou, Minrui Fei, Abdul Sadka, Yi Zhang, Xuelong Li

Research output: Contribution to journalArticle

26 Citations (Scopus)
242 Downloads (Pure)

Abstract

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.
Original languageEnglish
Pages (from-to)3552–3567
Number of pages16
JournalPattern Recognition
Volume47
Issue number11
Early online date20 May 2014
DOIs
Publication statusPublished - Nov 2014

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