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Visual Attention: low level and high level viewpoints

Stentiford, FWM; (2012) Visual Attention: low level and high level viewpoints. In: Schelkens, P and Ebrahimi, T and Cristobal, G and Truchetet, F and Saarikko, P, (eds.) Optics, Photonics, and Digital Technologies for Multimedia Applications II. (pp. 84360L). SPIE-INT SOC OPTICAL ENGINEERING Green open access

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Abstract

This paper provides a brief outline of the approaches to modeling human visual attention. Bottom-up and top-down mechanisms are described together with some of the problems that they face. It has been suggested in brain science that memory functions by trading measurement precision for associative power; sensory inputs from the environment are never identical on separate occasions, but the associations with memory compensate for the differences. A graphical representation for image similarity is described that relies on the size of maximally associative structures (cliques) that are found to reflect between pairs of images. This is applied to the recognition of movie posters, the location and recognition of characters, and the recognition of faces. The similarity mechanism is shown to model popout effects when constraints are placed on the physical separation of pixels that correspond to nodes in the maximal cliques. The effect extends to modeling human visual behaviour on the Poggendorff illusion.

Type: Proceedings paper
Title: Visual Attention: low level and high level viewpoints
Location: Brussels, BELGIUM
Open access status: An open access version is available from UCL Discovery
DOI: 10.1117/12.923511
Publisher version: http://dx.doi.org/10.1117/12.923511
Language: English
Additional information: © (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only. This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Science & Technology, Technology, Physical Sciences, Engineering, Electrical & Electronic, Optics, Physics, Applied, Engineering, Physics, Visual attention, pattern recognition, top-down, bottom-up, popout, cliques, Saliency,
UCL classification: UCL > School of BEAMS
UCL > School of BEAMS > Faculty of Engineering Science
URI: http://discovery.ucl.ac.uk/id/eprint/1360905
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