QUT ePrints

A visual attention approach to personal identification

Maeder, Anthony J. & Fookes, Clinton B. (2003) A visual attention approach to personal identification. In Eighth Australian and New Zealand Intelligent Information Systems Conference, 10-12 December 2003.

Abstract

This paper describes the use of visual attention characteristics, monitored by gaze tracking during presentation of a known visual scene to a viewer, as a biometric for distinguishing between individual viewers. The positions and sequences of gaze locations during viewing may be determined by overt (conscious) or covert (sub-conscious) viewing behaviour. Methods to quantify the spatial and temporal patterns established by the viewer for a particular image are proposed, and distance measures between these are established. Experimental results suggest that both types of gaze behaviours can provide simple and effective biometrics for this application.

Impact and interest:

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

92 since deposited on 17 Feb 2009
20 in the past twelve months

Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 17897
Item Type: Conference Paper
Keywords: Visual Attention, Personal Identification, Gaze
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Artificial Intelligence and Image Processing not elsewhere classified (080199)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2003 [please consult the authors]
Deposited On: 17 Feb 2009 11:35
Last Modified: 09 Jun 2010 23:22

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page