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

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2015-01-01

Author

Gundogdu, Erhan
Ozkan, Huseyin
Demir, H. Seckin
Ergezer, Hamza
Akagündüz, Erdem
Pakin, S. Kubilay

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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.

URI

https://hdl.handle.net/11511/93580

DOI

https://doi.org/10.1109/cvprw.2015.7301290

Conference Name

IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

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Graduate School of Informatics, Conference / Seminar

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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.