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Novelty Analysis in Dynamic Scene for Autonomous Mental Development

  • Sang-Woo Ban
  • Minho Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3696)

Abstract

We propose a new biologically motivated novelty analysis model that can give robust performance for natural scenes with affine transformed field of view as well as noisy scenes in dynamic visual environment, which can play important role for an autonomous mental development. The proposed model based on biological visual pathway uses a topology matching method of a visual scan path obtained from a low level top-down attention model in conjunction with a bottom-up saliency map model in order to detect a novelty in an input scene. In addition, the energy signature for the corresponding visual scan path is also considered to decide whether a novelty is occurred in an input scene or not. The computer experimental results show that the proposed model successfully indicates a novelty for natural color input scenes in dynamic visual environment.

Keywords

Lateral Geniculate Nucleus Attention Model Dynamic Scene Novelty Detection Fuzzy ARTMAP 
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 2005

Authors and Affiliations

  • Sang-Woo Ban
    • 1
  • Minho Lee
    • 1
  1. 1.School of Electrical Engineering and Computer ScienceKyungpook National UniversityTaeguKorea

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