Comparison of Infrared and Visible Imagery for Object Tracking: Toward Trackers with Superior IR Performance

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2015-01-01
Gundogdu, Erhan
Ozkan, Huseyin
Demir, H. Seckin
Ergezer, Hamza
Akagündüz, Erdem
Pakin, S. Kubilay
The subject of this paper is the visual object tracking in infrared (IR) videos. Our contribution is twofold. First, the performance behaviour of the state-of-the-art trackers is investigated via a comparative study using IR-visible band video conjugates, i.e., video pairs captured observing the same scene simultaneously, to identify the IR specific challenges. Second, we propose a novel ensemble based tracking method that is tuned to IR data. The proposed algorithm sequentially constructs and maintains a dynamical ensemble of simple correlators and produces tracking decisions by switching among the ensemble correlators depending on the target appearance in a computationally highly efficient manner We empirically show that our algorithm significantly outperforms the state-of-the-art trackers in our extensive set of experiments with IR imagery.

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Citation Formats
E. Gundogdu, H. Ozkan, H. S. Demir, H. Ergezer, E. Akagündüz, and S. K. Pakin, “Comparison of Infrared and Visible Imagery for Object Tracking: Toward Trackers with Superior IR Performance,” presented at the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Massachusetts, Amerika Birleşik Devletleri, 2015, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/93580.