Acta Optica Sinica, Volume. 30, Issue 5, 1291(2010)
Infrared Object Tracking Based on Adaptive Multi-Features Integration
Designing on effective observation model to discriminate object region from complex background is the core of robust tracking. A tracking approach based on multi-features observation has been proposed for infrared image sequences. Object appearance is represented by gray value,local standard deviation and gradient features in a unified histogram form;a scence-adaptive weighting scheme for these three features is used to construct the observation model,the selection of these multifeatures weights is towards the direction of maximizing discriminability between the target and its adjacent background. Experimental results on real complex situation demonstrate that the proposed algorithm tracks target well in highly appearance changes and severe clutter.
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Zhang Hui, Zhao Baojun, Tang Linbo, Li Jianke. Infrared Object Tracking Based on Adaptive Multi-Features Integration[J]. Acta Optica Sinica, 2010, 30(5): 1291
Category: Image Processing
Received: May. 31, 2009
Accepted: --
Published Online: May. 11, 2010
The Author Email: Hui Zhang (huizee@bit.edu.cn)