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Top-Down Object Color Biased Attention Using Growing Fuzzy Topology ART

  • Byungku Hwang
  • Sang-Woo Ban
  • Minho Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5326)

Abstract

In this paper, we propose a top-down object biased attention model which is based on human visual attention mechanism integrating feature based bottom-up attention and goal based top-down attention. The proposed model can guide attention to focus on a given target colored object over other objects or feature based salient areas by considering the object color biased attention mechanism. We proposed a growing fuzzy topology ART that plays important roles for object color biased attention, one of which is to incrementally learn and memorize features of arbitrary objects and the other one is to generate top-down bias signal by competing memorized features of a given target object with features of an arbitrary object. Experimental results show that the proposed model performs well in successfully focusing on given target objects, as well as incrementally perceiving arbitrary objects in natural scenes.

Keywords

Top-down object color biased attention bottom-up attention growing fuzzy topology ART 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Byungku Hwang
    • 1
  • Sang-Woo Ban
    • 2
  • Minho Lee
    • 1
  1. 1.School of Electrical Engineering and Computer ScienceKyungpook National UniversityPuk-GuKorea
  2. 2.Dept. of Information and Communication EngineeringDongguk UniversityGyeongjuKorea

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