A multi-texture approach for estimating iris positions in the eye using 2.5D Active Appearance Models

Hanan Salam, Nicolas Stoiber, Renaud Seguier

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes a new approach for the detection of the iris center. Starting from a learning base that only contains people in frontal view and looking in front of them, our model (based on 2.5D Active Appearance Models (AAM)) is capable of capturing the iris movements for both people in frontal view and with different head poses. We merge an iris model and a local eye model where holes are put in the place of the white-iris region. The iris texture slides under the eye hole permitting to synthesize and thus analyze any gaze direction. We propose a multi-objective optimization technique to deal with large head poses. We compared our method to a 2.5D AAM trained on faces with different gaze directions and showed that our proposition outperforms it in robustness and accuracy of detection specifically when head pose varies and with subjects wearing eyeglasses.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages1833-1836
Number of pages4
DOIs
StatePublished - 2012
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: Sep 30 2012Oct 3 2012

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Other

Other2012 19th IEEE International Conference on Image Processing, ICIP 2012
Country/TerritoryUnited States
CityLake Buena Vista, FL
Period9/30/1210/3/12

Keywords

  • Active appearance model
  • gaze detection
  • iris tracking

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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