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Learning High-Level Visual Concepts Using Attributed Primitives and Genetic Programming

  • Krzysztof Krawiec
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3907)

Abstract

In this paper, we present a novel approach to genetic learning of high-level visual concepts that works with sets of attributed visual primitives rather than with raster images. The paper presents the approach in detail and verifies it in an experiment concerning locating objects in real-world 3D scenes.

Keywords

Genetic Programming Child Node Gabor Filter Raster Image Pattern Recognition System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Krzysztof Krawiec
    • 1
  1. 1.Institute of Computing SciencePoznań University of TechnologyPoznańPoland

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