A computer vision model for visual-object-based attention and eye movements

Yaoru Sun, Robert Fisher, Fang Wang, Herman Martins Gomes

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

This paper presents a new computational framework for modelling visual-object-based attention and attention-driven eye movements within an integrated system in a biologically inspired approach. Attention operates at multiple levels of visual selection by space, feature, object and group depending on the nature of targets and visual tasks. Attentional shifts and gaze shifts are constructed upon their common process circuits and control mechanisms but also separated from their different function roles, working together to fulfil flexible visual selection tasks in complicated visual environments. The framework integrates the important aspects of human visual attention and eye movements resulting in sophisticated performance in complicated natural scenes. The proposed approach aims at exploring a useful visual selection system for computer vision, especially for usage in cluttered natural visual environments.
Original languageEnglish
Pages (from-to)126-142
Number of pages17
JournalComputer Vision and Image Understanding
Issue number2
Early online date21 Feb 2008
Publication statusPublished - Nov 2008

Keywords / Materials (for Non-textual outputs)

  • Attention-driven eye movements
  • Foveated imaging
  • Group-based attention
  • Object-based attention
  • Space-based attention
  • Visual-object-based competition


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