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Proceedings Paper

Target tracking algorithm based on Kalman filter and optimization MeanShift
Author(s): Heng Wu; Tao Han; Jie Zhang
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Paper Abstract

Background change ,shape change and target covering will all cause target tracking failure. Real-time and accuracy in target tracking is the problem that must be considered. This paper first presents the Mean Shift algorithm, then the Mean Shift algorithm iterative weight is modified with main information more prominent, secondary information suppressed, avoiding the tedious root, improving the real-time and effectiveness of target tracking:The target template updating algorithm is present to solve change of background and target shape change. Then a Kalman filter in the horizontal position and the vertical position is established to solve the problem of target tracking completely covered. Simulation results show that target tracking algorithm on the condition of target template update has higher tracking accuracy , higher real-time property and at the same time is robust than the traditional Mean Shift tracking algorithm .

Paper Details

Date Published: 15 November 2017
PDF: 10 pages
Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 1060526 (15 November 2017); doi: 10.1117/12.2292720
Show Author Affiliations
Heng Wu, Chinese Flight Test Establishment (China)
Tao Han, Chinese Flight Test Establishment (China)
Jie Zhang, Chinese Flight Test Establishment (China)


Published in SPIE Proceedings Vol. 10605:
LIDAR Imaging Detection and Target Recognition 2017
Yueguang Lv; Weimin Bao; Weibiao Chen; Zelin Shi; Jianzhong Su; Jindong Fei; Wei Gong; Shensheng Han; Weiqi Jin; Jian Yang, Editor(s)

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