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Object recognition using multidimensional receptive field histograms

  • Bernt Schiele
  • James L. Crowley
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1064)

Abstract

This paper presents a technique to determine the identity of objects in a scene using histograms of the responses of a vector of local linear neighborhood operators (receptive fields). This technique can be used to determine the most probable objects in a scene, independent of the object's position, image-plane orientation and scale. In this paper we describe the mathematical foundations of the technique and present the results of experiments which compare robustness and recognition rates for different local neighborhood operators and histogram similarity measurements.

Keywords

Receptive Field Object Recognition Recognition Rate Color Histogram Gabor Filter 
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 1996

Authors and Affiliations

  • Bernt Schiele
    • 1
  • James L. Crowley
    • 1
  1. 1.LIFIA/GRAVIRGrenobleFrance

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