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International Journal of Computer Vision

, Volume 14, Issue 2, pp 119–130 | Cite as

Context-free attentional operators: The generalized symmetry transform

  • Daniel Reisfeld
  • Haim Wolfson
  • Yehezkel Yeshurun
Article

Abstract

Active vision systems, and especially foveated vision systems, depend on efficient attentional mechanisms. We propose that machine visual attention should consist of both high-level, context-dependent components, and low-level, context free components. As a basis for the context-free component, we present an attention operator based on the intuitive notion of symmetry, which generalized many of the existing methods of detecting regions of interest. It is a low-level operator that can be applied successfully without a priori knowledge of the world. The resultingsymmetry edge map can be applied in various low, intermediate-and high- level tasks, such as extraction of interest points, grouping, and object recognition. In particular, we have implemented an algorithm that locates interest points in real time, and can be incorporated in active and purposive vision systems. The results agree with some psychophysical findings concerning symmetry as well as evidence concerning selection of fixation points. We demonstrate the performance of the transform on natural, cluttered images.

Keywords

Computer Vision Vision System Computer Image Object Recognition Visual Attention 
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

© Kluwer Academic Publishers 1995

Authors and Affiliations

  • Daniel Reisfeld
    • 1
  • Haim Wolfson
    • 1
  • Yehezkel Yeshurun
    • 1
  1. 1.Computer Science Department, Sackler Faculty of Exact SciencesTel Aviv UniversityIsrael

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