Multi-Objective Forecast Track Based on Kalman-Camshift Algorithm

Abstract:

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In carries on the multi-objective movement track, because often the goal covers, factors and so on merge, separation to cause the track defeat. Proposed with the dynamic background modeling technology and the RGB three channel chromatic aberration law gain target complex group, then uses the Kalman filter forecast movement goal initial parameter, uses the improvement the Camshift algorithm to iterate gradually again approaches each goal exact location, has realized to the multi-objective auto-adapted tracks. The massive experiments indicated that this algorithm robustness is good, auto-adapted ability.

Info:

Periodical:

Advanced Materials Research (Volumes 211-212)

Edited by:

Ran Chen

Pages:

137-141

Citation:

J. B. Qu et al., "Multi-Objective Forecast Track Based on Kalman-Camshift Algorithm", Advanced Materials Research, Vols. 211-212, pp. 137-141, 2011

Online since:

February 2011

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Price:

$38.00

[1] Wei Yang and Qi Chai: Electro-Optic Technology Application Vol. 5(2009), pp.275-278, in Chinese.

[2] A.R. Mansouri and J. Konrad: IEEE Transactions on Image Processing Vol. 2(2003), pp.201-220.

[3] S.L. Dockstader and A.M. Tekalp: IEEE Workshop on Multi-Object Tracking Vol. 3(2001), pp.95-102.

[4] Baisheng Chen: Computer Engineering and Applications Vol. 2(2006), pp.46-47, in Chinese.

[5] D. Comaniciu, V. Ramesh and P. Mee: IEEE Conference on Computer Vision and Pattern Recognition Vol. 5(2000), pp.142-149.

[6] D. Comaniciu: IEEE Transactions on Pattern Analysis and Machine Intelligence Vol. 2(2003), pp.564-577.

[7] D.G. Sim, O.K. Kwon and R.H. Park: IEEE Transactions on Image Processing Vol. 3(1999), pp.425-429.

[8] M.S. Arulampalam, S. Maskell and N. Gordon: IEEE Transactions on Signal Processing Vol. 2 (2002), pp.174-188.

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