Real-time target tracking with particle filter in moving monocular camera

Guocheng Liu; Yongji Wang

doi:10.1117/12.748329

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15 November 2007 Real-time target tracking with particle filter in moving monocular camera

Guocheng Liu, Yongji Wang

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Proceedings Volume 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition; 67861G (2007) https://doi.org/10.1117/12.748329
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

In this paper, we propose an improved particle filter algorithm for real-time tracking a randomly moving target in dynamic environment with a moving monocular camera. For making the tracking task robustly and effectively, color histogram based target model is integrated into particle filter algorithm. Bhattacharyya distance is used to weight samples by calculating each sample's histogram with a specified target model and it makes the measurement matching and samples' weight updating more reasonable. In order to reduce sample depletion, the improved algorithm will be able to take the latest observation into account. The experimental results confirm that the method is effective even when the monocular camera is moving and the target object is partially occluded in a clutter background.

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Guocheng Liu and Yongji Wang "Real-time target tracking with particle filter in moving monocular camera", Proc. SPIE 6786, MIPPR 2007: Automatic Target Recognition and Image Analysis; and Multispectral Image Acquisition, 67861G (15 November 2007); https://doi.org/10.1117/12.748329

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