Adaptive fusion of particle filtering and spatio-temporal motion energy for human tracking

PATTERN RECOGNITION

卷:47

Article

Zhou, Huiyu¹  Fei, Minrui²  Sadka, Abdul³  Zhang, Yi⁴  Li, Xuelong⁵ 

[1] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT3 9DT, Antrim, North Ireland

[2] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200041, Peoples R China

[3] Brunel Univ, Sch Engn & Design, Uxbridge UB8 3PH, Middx, England

[4] Chongqing Univ Post & Telecommun, Inst Automat, Chongqing, Peoples R China

[5] Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr Opt IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China

关键词: Computer vision;    Object tracking;    Occlusion;    Colour;    Motion energy;   

DOI  :  10.1016/j.patcog.2014.05.006

来源: Elsevier

【 摘 要 】

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. (C) 2014 Elsevier Ltd. All rights reserved.

【 授权许可】

Free