Research on target tracking based on improved SURF algorithm and Kalman prediction

Dandan Hu; Jiang Nan

doi:10.1117/12.2242830

11 July 2016 Research on target tracking based on improved SURF algorithm and Kalman prediction

Dandan Hu, Jiang Nan

Proceedings Volume 10011, First International Workshop on Pattern Recognition; 1001102 (2016) https://doi.org/10.1117/12.2242830
Event: First International Workshop on Pattern Recognition, 2016, Tokyo, Japan

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.

Citation Download Citation

Dandan Hu and Jiang Nan "Research on target tracking based on improved SURF algorithm and Kalman prediction", Proc. SPIE 10011, First International Workshop on Pattern Recognition, 1001102 (11 July 2016); https://doi.org/10.1117/12.2242830

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