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Linwu Liu

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Proceedings Article | 12 October 2020 Paper

The correlation filter tracking algorithm using multi-feature background perception

Yuantao Chen, Volachith Phonevilay, Linwu Liu, Jiajun Tao

Proceedings Volume 11574, 115740P (2020) https://doi.org/10.1117/12.2577002

KEYWORDS: Detection and tracking algorithms, Electronic filtering, Image filtering, Optical tracking, Feature extraction, Video, Optical filters, Dimension reduction, Visualization

Read Abstract +

For visual object tracking in the block motion blur deformation background interference and other issues, put forward in combination with characteris-tics of multiple characteristic scale estimate of background perception related filter tracking algorithm, it through in the object area will be the basis of original algorithm and expand, increase extraction Histogram of Oriented Gradient (HOG) and the characteristics of Color Names (CN) to learn more background information filter, improve object localization accuracy. On this basis, the binary matrix is reasonably constructed to improve the effective response of the filter to the object region on the premise of effectively sup-pressing the background, and the size of the object is estimated by using the training scale filter. Experimental and simulation results show that the pro-posed algorithm can solve the problems such as background interference of occlusive motion blur deformation in tracking. In OTB-100 datasets, the ac-curacy and success rate of proposed algorithm are improved by 1.3% and 1.4% respectively. In the background interference sequence of occluding mo-tion blur deformation of OTB-100 datasets, the accuracy of the proposed al-gorithm is 1.9%, 4.0%, 4.3% and 3.4% higher than that of the Backline-Aware Correlation Filters (BACF) algorithm. The FPS can reach 13.7, this result can show that it has high theoretical value and engineering value.

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