UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Saliency identified by absence of background structure

Stentiford, F; (2013) Saliency identified by absence of background structure. In: Human Vision and Electronic Imaging XVIII. (pp. 86510V). SPIE: Burlingame, California, U.S.. Green open access

[thumbnail of Stentiford_86510V.pdf]
Preview
Text
Stentiford_86510V.pdf - Published Version

Download (415kB) | Preview

Abstract

Visual attention is commonly modelled by attempting to characterise objects using features that make them special or in some way distinctive in a scene. These approaches have the disadvantage that it is never certain what features will be relevant in an object that has not been seen before. This paper provides a brief outline of the approaches to modeling human visual attention together with some of the problems that they face. A graphical representation for image similarity is described that relies on the size of maximally associative structures (cliques) that are found to be reflected in pairs of images. While comparing an image with itself, the similarity mechanism is shown to model pop-out effects when constraints are placed on the physical separation of pixels that correspond to nodes in the maximal cliques. Background regions are found to contain structure in common that is not present in the salient regions which are thereby identified by its absence. The approach is illustrated with figures that exemplify asymmetry in pop-out, the conjunction of features, orientation disturbances and the application to natural images.

Type: Proceedings paper
Title: Saliency identified by absence of background structure
Event: IS&T/SPIE Electronic Imaging 2013
Location: San Francisco, US
Dates: 03 February 2013 - 07 February 2013
Open access status: An open access version is available from UCL Discovery
DOI: 10.1117/12.2002085
Publisher version: http://dx.doi.org/10.1117/12.2002085
Language: English
Additional information: © 2013. 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: Visual attention, saliency, pattern recognition, similarity, pop-out, cliques
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
URI: https://discovery.ucl.ac.uk/id/eprint/1546243
Downloads since deposit
0Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item