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Engineering of Computer Vision Algorithms Using Evolutionary Algorithms

  • Conference paper
Advanced Concepts for Intelligent Vision Systems (ACIVS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5807))

Abstract

Computer vision algorithms are currently developed by looking up the available operators from the literature and then arranging those operators such that the desired task is performed. This is often a tedious process which also involves testing the algorithm with different lighting conditions or at different sites. We have developed a system for the automatic generation of computer vision algorithms at interactive frame rates using GPU accelerated image processing. The user simply tells the system which object should be detected in an image sequence. Simulated evolution, in particular Genetic Programming, is used to automatically generate and test alternative computer vision algorithms. Only the best algorithms survive and eventually provide a solution to the user’s image processing task.

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Author information

Authors and Affiliations

  1. Wilhelm-Schickard-Institut für Informatik, Eberhard Karls Universität Tübingen, Abt. Rechnerarchitektur, Sand 1, 72076, Tübingen, Germany

    Marc Ebner

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  1. Marc Ebner
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Editor information

Editors and Affiliations

  1. DGA/D4S/MRIS, CEP/GIP, 16 bis avenue Prieur de la côte d’or., 94114, Arcueil, France

    Jacques Blanc-Talon

  2. Department of Telecommunication and Information Processing, Ghent University, St.-Pietersnieuwstraat 41, 9000, Gent, Belgium

    Wilfried Philips

  3. CSIRO ICT Centre, Epping, Po Box 76, 1710, Sydney, NSW, Australia

    Dan Popescu

  4. University of Antwerp, Universiteitsplein 1; Building N., 2610, Wilrijk, Belgium

    Paul Scheunders

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© 2009 Springer-Verlag Berlin Heidelberg

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Ebner, M. (2009). Engineering of Computer Vision Algorithms Using Evolutionary Algorithms. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04697-1_34

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  • DOI: https://doi.org/10.1007/978-3-642-04697-1_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04696-4

  • Online ISBN: 978-3-642-04697-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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