Video-based biometric identification using eye tracking technique

Zhen Liang, Fei Tan, Zheru Chi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

30 Citations (Scopus)

Abstract

Recently, biometric identification techniques have attracted great attention due to increasing demand of high-performance security systems. Compared with conventional identification methods, biometric techniques provide more reliable and robust solutions. In this paper, a novel video-based biometric identification model based on eye tracking technique is proposed. Inspired by visual attention, video clips are designed for subjects to view in order to capture eye tracking data reflecting their physiological and behavioral characteristics. Various visual attention characteristics, including acceleration, geometric, and muscle properties, are extracted from eye gaze data and used as biometric features to identify persons. An algorithm based on mutual information of features is adopted to perform feature evaluation for obtaining a set of the most discriminative features for biometric identification. Experiments are conducted by using two types of classifiers, Back-Propagation (BP) neural network and Support Vector Machine (SVM). Experimental results show that using video-based eye tracking data for biometric identification is feasible. In particular, eye tracking can be used as an additional biometric modal to enhance the performance of current biometric person identification systems.
Original languageEnglish
Title of host publication2012 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2012
Pages728-733
Number of pages6
DOIs
Publication statusPublished - 26 Nov 2012
Event2012 2nd IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2012 - Hong Kong, Hong Kong
Duration: 12 Aug 201215 Aug 2012

Conference

Conference2012 2nd IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2012
Country/TerritoryHong Kong
CityHong Kong
Period12/08/1215/08/12

Keywords

  • Biometric identification
  • video-based eye tracking
  • visual attention characteristics

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

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