Forward-looking infrared 3D target tracking via combination of particle filter and SIFT

Xing Li; Zhiguo Cao; Ruicheng Yan; Tuo Li

doi:10.1117/12.2031019

26 October 2013 Forward-looking infrared 3D target tracking via combination of particle filter and SIFT

Xing Li, Zhiguo Cao, Ruicheng Yan, Tuo Li

Proceedings Volume 8918, MIPPR 2013: Automatic Target Recognition and Navigation; 891808 (2013) https://doi.org/10.1117/12.2031019
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China

Abstract

Aiming at the problem of tracking 3D target in forward-looking infrared (FLIR) image, this paper proposes a high-accuracy robust tracking algorithm based on SIFT and particle filter. The main contribution of this paper is the proposal of a new method of estimating the affine transformation matrix parameters based on Monte Carlo methods of particle filter. At first, we extract SIFT features on infrared image, and calculate the initial affine transformation matrix with optimal candidate key points. Then we take affine transformation parameters as particles, and use SIR (Sequential Importance Resampling) particle filter to estimate the best position, thus implementing our algorithm. The experiments demonstrate that our algorithm proves to be robust with high accuracy.

Citation Download Citation

Xing Li, Zhiguo Cao, Ruicheng Yan, and Tuo Li "Forward-looking infrared 3D target tracking via combination of particle filter and SIFT", Proc. SPIE 8918, MIPPR 2013: Automatic Target Recognition and Navigation, 891808 (26 October 2013); https://doi.org/10.1117/12.2031019

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