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Experimental Comparative Evaluation of Feature Point Tracking Algorithms

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Performance Characterization in Computer Vision

Part of the book series: Computational Imaging and Vision ((CIVI,volume 17))

Abstract

We consider dynamic scenes with multiple, independently moving objects. The objects are represented by feature points whose motion is tracked in long image sequences. The feature points may temporarily disappear, enter and leave the view field. This situation is typical for surveillance, scene monitoring (Courtney, 1997) and some other applications.

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References

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Author information

Authors and Affiliations

  1. Computer and Automation Research Institute, Kende u.13-17, Budapest, H-1111, Hungary

    Judit Verestóy & Dmitry Chetverikov

Authors
  1. Judit Verestóy
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  2. Dmitry Chetverikov
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Tamaki Campus, The University of Auckland, Private Bag 92019, Auckland, New Zealand

    Reinhard Klette

  2. Cognitive Systems Research Group, Department of Computer Science, University of Hamburg, Hamburg, Germany

    H. Siegfried Stiehl

  3. FB Informatik AB Kognitive Systeme, Universität Hamburg, Vogt-Kölln-Str. 30, D-22527, Hamburg, Germany

    H. Siegfried Stiehl

  4. Image Sciences Institute, University Medical Center Utrecht, E01.334 Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands

    Max A. Viergever  & Koen L. Vincken  & 

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© 2000 Springer Science+Business Media Dordrecht

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Verestóy, J., Chetverikov, D. (2000). Experimental Comparative Evaluation of Feature Point Tracking Algorithms. In: Klette, R., Stiehl, H.S., Viergever, M.A., Vincken, K.L. (eds) Performance Characterization in Computer Vision. Computational Imaging and Vision, vol 17. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9538-4_14

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  • DOI: https://doi.org/10.1007/978-94-015-9538-4_14

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-5487-6

  • Online ISBN: 978-94-015-9538-4

  • eBook Packages: Springer Book Archive

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