A Novel Performance Evaluation Methodology for Single-Target Trackers

IEEE Transactions on Pattern Analysis and Machine Intelligence
Matej KristanLuka Cehovin

Abstract

This paper addresses the problem of single-target tracker performance evaluation. We consider the performance measures, the dataset and the evaluation system to be the most important components of tracker evaluation and propose requirements for each of them. The requirements are the basis of a new evaluation methodology that aims at a simple and easily interpretable tracker comparison. The ranking-based methodology addresses tracker equivalence in terms of statistical significance and practical differences. A fully-annotated dataset with per-frame annotations with several visual attributes is introduced. The diversity of its visual properties is maximized in a novel way by clustering a large number of videos according to their visual attributes. This makes it the most sophistically constructed and annotated dataset to date. A multi-platform evaluation system allowing easy integration of third-party trackers is presented as well. The proposed evaluation methodology was tested on the VOT2014 challenge on the new dataset and 38 trackers, making it the largest benchmark to date. Most of the tested trackers are indeed state-of-the-art since they outperform the standard baselines, resulting in a highly-challenging benchmark. An exhau...Continue Reading

References

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Citations

Sep 16, 2016·Frontiers in Neuroscience·Yuhuang HuTobi Delbruck
Mar 31, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Jiatong LiBaojun Zhao
Mar 10, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Stefan Duffner, Christophe Garcia
Jul 6, 2017·IEEE Transactions on Cybernetics·Alan LukezicMatej Kristan
Sep 1, 2017·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society· Qing Guo Bin Wu
May 1, 2019·Sensors·Hong ZhangDaniel Sun
Aug 2, 2017·International Journal of Multimedia Information Retrieval·George AwadShin'ichi Satoh
Jan 1, 2018·International Journal of Computer Vision·Grigorios G ChrysosStefanos Zafeiriou

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