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Fast template matching based on deformable best-buddies similarity measure

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Abstract

Accuracy and speed are the essential metrics for the template matching algorithms in solving object tracking problems. Since the method based on Best Buddies Similarity (BBS) has achieved the state-of-the-art performance in terms of accuracy, matching speed becomes the shortest piece of wood of the bucket. In this paper, we propose a fast template matching method based on our deformable BBS measure. The deformable BBS measure enables matching to be performed between the patches in varying sizes, and hence leads to even higher accuracy than the original BBS-based methods. More important, we develop a fast potential-area discovery algorithm based on proposal generation and selection. It significantly reduces the numbers of useless attempts on calculating and comparing similarities of impossible image patches. The experimental results show that, with the deformable BBS measure and the fast potential-area discovery, our template matching method outperforms the state-of-the-art methods in terms of accuracy, speed and robustness.

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Notes

  1. TB-50 Sequences are available at: http://cvlab.hanyang.ac.kr/tracker_benchmark/benchmark_v10.html

    2 VOT2016 benchmark is available at: http://www.votchallenge.net/vot2016/dataset.html

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (No.61762014), the Opening Project of Guangxi Colleges and Universities Key Laboratory of robot & welding (Guilin University of Aerospace Technology), the Opening Project of Shaanxi Key Laboratory of Complex Control System and Intelligent Information Processing, and the Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (MIMS15-05), and and the Research Fund of Guangxi Key Lab of intelligent integrated automation. This work is also partly supported by the National Natural Science Foundation of China (No.61762012 and No.61462026).

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Authors and Affiliations

  1. Guangxi Normal University, Guilin, China

    Haiying Xia, Wenxian Zhao, Frank Jiang, Haisheng Li & Zheng Zhou

  2. Guilin University of Aerospace Technology, Guilin, China

    Haiying Xia

  3. Guilin University of Electronic Technology, Guilin, China

    Haiying Xia

  4. China united network telecommunications Co. Ltd, Jining, China

    Wenxian Zhao

  5. Xi’an University of Technology, Xi’an, China

    Jing Xin

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  1. Haiying Xia
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Correspondence to Haiying Xia.

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Xia, H., Zhao, W., Jiang, F. et al. Fast template matching based on deformable best-buddies similarity measure. Multimed Tools Appl 78, 11905–11925 (2019). https://doi.org/10.1007/s11042-018-6722-x

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