Robust infrared target tracking using thermal information in mean-shift

Sungmin Yun; Sungho Kim

doi:10.1117/12.2519191

13 May 2019 Robust infrared target tracking using thermal information in mean-shift

Sungmin Yun, Sungho Kim

Author Affiliations +

Proceedings Volume 10995, Pattern Recognition and Tracking XXX; 1099509 (2019) https://doi.org/10.1117/12.2519191
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

The basic computational module of the technique is an old pattern recognition procedure: the mean-shift. In case of gray level feature domain, the spatial information of the target is lost when the background brightness histogram is the same as the target histogram. In this paper, we propose a new algorithm that is independent of background contrast by changing features from a conventional brightness based histogram to a temperature- based histogram. The proposed algorithm can track targets robustly regardless to target-background contrast. The experiment results demonstrate that the temperature-based Mean-Shift outperforms comparing with the brightness-based Mean-Shift when track a object with successive background variations.

Conference Presentation

Citation Download Citation

Sungmin Yun and Sungho Kim "Robust infrared target tracking using thermal information in mean-shift", Proc. SPIE 10995, Pattern Recognition and Tracking XXX, 1099509 (13 May 2019); https://doi.org/10.1117/12.2519191

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