This is the matlab code of SAMF[1]. It won the second place in VOT 2014. The implementation is built upon the code of [2]. The codes provided by [3,4,5] are also used in the implementation.
#Instructions:
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- Modify the base_path in "run_tracker.m" with your own setting.
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- Run the "run_tracker.m" script in MATLAB.
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- Choose sequence.
#Acknowledge: Many thanks to Guy Koren and Jifeng Ning(宁纪锋) for helping me to find and fix bugs!
#Contact: Yang Li, liyang89@zju.edu.cn ihpdep.github.io
Jianke Zhu jkzhu@zju.edu.cn jkzhu.github.io
#Reference [1] Yang Li, Jianke Zhu. "A Scale Adaptive Kernel Correlation Filter Tracker with Feature Integration" European Conference on Computer Vision, Workshop VOT2014 (ECCVW), 2014
[2] J. F. Henriques, R. Caseiro, P. Martins, J. Batista. "High-Speed Tracking with Kernelized Correlation Filters." TPAMI - IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
[3] Martin Danelljan, Fahad Shahbaz Khan, Michael Felsberg and Joost van de Weijer. "Adaptive Color Attributes for Real-Time Visual Tracking". Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.
[4] J. van de Weijer, C. Schmid, J. J. Verbeek, and D. Larlus. "Learning color names for real-world applications." TIP, 18(7):1512–1524, 2009.
[5] David Ross, Jongwoo Lim, Ruei-Sung Lin, Ming-Hsuan Yang. "Incremental Learning for Robust Visual Tracking" In the International Journal of Computer Vision, Special Issue: Learning for Vision, 2007.