• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Extended kernel correlation filter for abrupt motion tracking

Vol. 11, No.9, September 30, 2017
10.3837/tiis.2017.09.014, Download Paper (Free):

Abstract

The Kernelized Correlation Filters (KCF) tracker has caused the extensive concern in recent years because of the high efficiency. Numerous improvements have been made successively. However, due to the abrupt motion between the consecutive image frames, these methods cannot track object well. To cope with the problem, we propose an extended KCF tracker based on swarm intelligence method. Unlike existing KCF-based trackers, we firstly introduce a swarm-based sampling method to KCF tracker and design a unified framework to track smooth or abrupt motion simultaneously. Secondly, we propose a global motion estimation method, where the exploration factor is constructed to search the whole state space so as to adapt abrupt motion. Finally, we give an adaptive threshold in light of confidence map, which ensures the accuracy of the motion estimation strategy. Extensive experimental results in both quantitative and qualitative measures demonstrate the effectiveness of our proposed method in tracking abrupt motion.


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Cite this article

[IEEE Style]
Huanlong Zhang, Jianwei Zhang, Qinge Wu, Xiaoliang Qian, Tong Zhou and Hengcheng FU, "Extended kernel correlation filter for abrupt motion tracking," KSII Transactions on Internet and Information Systems, vol. 11, no. 9, pp. 4438-4460, 2017. DOI: 10.3837/tiis.2017.09.014

[ACM Style]
Zhang, H., Zhang, J., Wu, Q., Qian, X., Zhou, T., and FU, H. 2017. Extended kernel correlation filter for abrupt motion tracking. KSII Transactions on Internet and Information Systems, 11, 9, (2017), 4438-4460. DOI: 10.3837/tiis.2017.09.014