Object detection for computer vision using a robust genetic algorithm

  • Authors:
  • Tania Mezzadri Centeno;Heitor Silvério Lopes;Marcelo Kleber Felisberto;Lúcia Valéria Ramos de Arruda

  • Affiliations:
  • CPGEI/CEFET-PR, Curitiba, PR, Brazil;CPGEI/CEFET-PR, Curitiba, PR, Brazil;CPGEI/CEFET-PR, Curitiba, PR, Brazil;CPGEI/CEFET-PR, Curitiba, PR, Brazil

  • Venue:
  • EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
  • Year:
  • 2005

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Abstract

This work is concerned with the development and implementation of an image pattern recognition approach to support computational vision systems when it is necessary to automatically check the presence of specific objects on a scene, and, besides, to describe their position, orientation and scale. The developed methodology involves the use of a genetic algorithm to find known 2D object views in the image. The proposed approach is fast and presented a robust performance in several test instances including multiobject scenes, with or without partial occlusion.