Adaptive kernelized correlation ﬁlter algorithm and application in target tracking

Fengfa Yue; Xingfei Li

doi:10.1117/12.2296485

12 January 2018 Adaptive kernelized correlation ﬁlter algorithm and application in target tracking

Fengfa Yue, Xingfei Li

Proceedings Volume 10621, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems; 1062109 (2018) https://doi.org/10.1117/12.2296485
Event: International Conference on Optical Instruments and Technology 2017, 2017, Beijing, China

Abstract

Adaptive kernelized correlation Filter (AKCF) approach is designed to achieve an accurate and stable tracking for the moving target with fast motion and background clutter. The proposed algorithm combines the advantages of adaptive threshold selection method and KCF algorithm. The adaptive threshold selection method can automatically select the appropriate threshold according to the size of the object in the image. The accuracy of KCF algorithm is improved by adaptive threshold selection method. The performance of AKCF is verified by some publicly available benchmark video sequences. The experiment results demonstrate that the proposed approach which has the performance accuracy and stability can effectively realize the stable tracking for fast moving target.

Citation Download Citation

Fengfa Yue and Xingfei Li "Adaptive kernelized correlation ﬁlter algorithm and application in target tracking", Proc. SPIE 10621, 2017 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 1062109 (12 January 2018); https://doi.org/10.1117/12.2296485

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KEYWORDS

Detection and tracking algorithms

Video

Optical tracking

Image filtering

Digital filtering

Electronic filtering

Video processing

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