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Proceedings Paper

Research on target tracking based on improved SURF algorithm and Kalman prediction
Author(s): Dandan Hu; Jiang Nan
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Paper Abstract

For the problem of ignoring color information and computing complexity and so on, a new target tracking algorithm based on improved SURF(Speed Up Robust Features) algorithm and Kalman filter fusion is studied. First, the color invariants are added in the generation process of SURF. And then the current position is predicted by using the Kalman filter and establishing the search window. Finally, the feature vectors in the search window are extracted by using the improved SURF algorithm for matching. The experiments prove that the algorithm can always track targets stably when the target appears scale changed, rotation and partial occlusion, and the tracking speed is greatly improved than that of the SURF algorithm.

Paper Details

Date Published: 11 July 2016
PDF: 6 pages
Proc. SPIE 10011, First International Workshop on Pattern Recognition, 1001102 (11 July 2016); doi: 10.1117/12.2242830
Show Author Affiliations
Dandan Hu, Civil Aviation Univ. of China (China)
Jiang Nan, Civil Aviation Univ. of China (China)

Published in SPIE Proceedings Vol. 10011:
First International Workshop on Pattern Recognition
Xudong Jiang; Guojian Chen; Genci Capi; Chiharu Ishll, Editor(s)

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