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


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Gundogdu E., Ozkan H., Demir H. S. , Ergezer H., Akagunduz E. , Pakin S. K.

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Massachusetts, United States Of America, 7 - 12 June 2015 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/cvprw.2015.7301290
  • City: Massachusetts
  • Country: United States Of America

Abstract

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.