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

Authors:
Yaoru Sun;Robert Fisher;Fang Wang;Herman Martins Gomes
Affiliations:
Nanjing University, China Brain and Behavioural Sciences Centre, University of Birmingham, Birmingham B15 2TT, UK;School of Informatics, University of Edinburgh, JCMB, The King's Buildings, Edinburgh EH9 3JZ, UK;The Intelligent Systems Lab, BT Exact, Ipswich IP5 3RE, UK;Universidade Federal de Campina Grande Departamento de Sistemas e Computação Av. Aprgio Veloso s/n 58109-970 Campina Grande PB, Brazil
Venue:
Computer Vision and Image Understanding
Year:
2008

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Abstract

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.