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Augmented Vision Perception in Infrared pp 113–137Cite as

Coalitional Tracker for Deception Detection in Thermal Imagery

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Part of the book series: Advances in Pattern Recognition ((ACVPR))

Abstract

We propose a novel tracking method that uses a network of independent particle filter trackers whose interactions are modeled using coalitional game theory. Our tracking method is general; it maintains pixel-level accuracy, and can negotiate surface deformations and occlusions. We tested our method in a substantial video set featuring nontrivial motion from over 40 objects in both the infrared and vi sual spectra. The coalitional tracker demonstrated fault-tolerant behavior that far exceeds the performance of single-particle filter trackers. Our method represents a shift from the typical tracking paradigms and may find application in demanding imaging problems across the electromagnetic spectrum.

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Author information

Authors and Affiliations

  1. Iconic Research, LLC, Houston, TX, USA

    Jonathan Dowdall

  2. Computational Physiology Lab, Department of Computer Science, University of Houston, Houston, TX, USA

    Ioannis Pavlidis

  3. Department of Statistics, Athens University of Economics and Business Athens, Greece

    Panagiotis Tsiamyrtzis

Authors
  1. Jonathan Dowdall
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  2. Ioannis Pavlidis
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  3. Panagiotis Tsiamyrtzis
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Editor information

Editors and Affiliations

  1. Delphi Electronics & Safety Kokomo, Indiana, USA

    Riad I. Hammoud

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© 2009 Springer-Verlag Berlin Heidelberg

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Dowdall, J., Pavlidis, I., Tsiamyrtzis, P. (2009). Coalitional Tracker for Deception Detection in Thermal Imagery. In: Hammoud, R.I. (eds) Augmented Vision Perception in Infrared. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84800-277-7_5

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  • DOI: https://doi.org/10.1007/978-1-84800-277-7_5

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84800-276-0

  • Online ISBN: 978-1-84800-277-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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