An improved adaptive video tracking method based on mean-shift

Yufeng Li; Fei Liu; Shaohu Gu

doi:10.1117/12.2036943

19 December 2013 An improved adaptive video tracking method based on mean-shift

Yufeng Li, Fei Liu, Shaohu Gu

Proceedings Volume 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology; 904505 (2013) https://doi.org/10.1117/12.2036943
Event: International Conference on Optical Instruments and Technology (OIT2013), 2013, Beijing, China

Abstract

For the mean shift tracking algorithm, we use the histogram feature which contains little information, but the moving direction and velocity information are not been considered, which leads to the target will be missed easily, what is more, the limitation of traditional algorithm which can not change the size of the window to adapt to the size of target, etc. To overcome those weaknesses, we introduce both the target feature representation idea having the features of adapting to window size adjustment and spatial characteristics and the nature of the kernel function, then, there is no need to estimate the probability for all regions. The results of experiment show that compared with using kalman filtering and mean shift algorithm alone, the weighted mean improved filtering algorithm has greatly improved the instability of target tracking and the robustness of the moving target tracking.

Citation Download Citation

Yufeng Li, Fei Liu, and Shaohu Gu "An improved adaptive video tracking method based on mean-shift", Proc. SPIE 9045, 2013 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, 904505 (19 December 2013); https://doi.org/10.1117/12.2036943

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KEYWORDS

Detection and tracking algorithms

Video

Image processing

Target detection

Automatic tracking

Statistical analysis

Electronic filtering

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