Real-time gaze tracking with appearance-based models

Psychological evidence has emphasized the importance of eye gaze analysis in human computer interaction and emotion interpretation. To this end, current image analysis algorithms take into consideration eye-lid and iris motion detection using colour information and edge detectors. However, eye movem...

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Detalles Bibliográficos
Autores: Orozco, Javier, Roca, F. Xavier, Gonzàlez, Jordi
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2009
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/30588
Acceso en línea:http://hdl.handle.net/10261/30588
Access Level:acceso abierto
Palabra clave:Eyelid and iris tracking
Appearance models
Blinking
Iris saccade
Real-time gaze tracking
Pattern recognition
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spelling Real-time gaze tracking with appearance-based modelsOrozco, JavierRoca, F. XavierGonzàlez, JordiEyelid and iris trackingAppearance modelsBlinkingIris saccadeReal-time gaze trackingPattern recognitionPsychological evidence has emphasized the importance of eye gaze analysis in human computer interaction and emotion interpretation. To this end, current image analysis algorithms take into consideration eye-lid and iris motion detection using colour information and edge detectors. However, eye movement is fast and and hence difficult to use to obtain a precise and robust tracking. Instead, our method proposed to describe eyelid and iris movements as continuous variables using appearance-based tracking. This approach combines the strengths of adaptive appearance models, optimization methods and backtracking techniques. Thus, in the proposed method textures are learned on-line from near frontal images and illumination changes, occlusions and fast movements are managed. The method achieves real-time performance by combining two appearance-based trackers to a backtracking algorithm for eyelid estimation and another for iris estimation. These contributions represent a significant advance towards a reliable gaze motion description for HCI and expression analysis, where the strength of complementary methodologies are combined to avoid using high quality images, colour information, texture training, camera settings and other time-consuming processes.This work is supported by EC grants IST-027110 for the HERMES project and IST-045547 for the VIDI-video project, by the Spanish MEC under projects TIN2006-14606 and CONSOLIDER INGENIO 2010 (CSD2007-00018). Jordi Gonzàlez also acknowledges the support of a Juan de la Cierva Postdoctoral fellowship from the Spanish MEC.Peer ReviewedSpringer Nature201020102009info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Postprintinfo:eu-repo/semantics/acceptedVersionhttp://hdl.handle.net/10261/30588reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Ingléshttp://dx.doi.org/10.1007/s00138-008-0130-6info:eu-repo/semantics/openAccessoai:digital.csic.es:10261/305882026-05-22T06:33:51Z
dc.title.none.fl_str_mv Real-time gaze tracking with appearance-based models
title Real-time gaze tracking with appearance-based models
spellingShingle Real-time gaze tracking with appearance-based models
Orozco, Javier
Eyelid and iris tracking
Appearance models
Blinking
Iris saccade
Real-time gaze tracking
Pattern recognition
title_short Real-time gaze tracking with appearance-based models
title_full Real-time gaze tracking with appearance-based models
title_fullStr Real-time gaze tracking with appearance-based models
title_full_unstemmed Real-time gaze tracking with appearance-based models
title_sort Real-time gaze tracking with appearance-based models
dc.creator.none.fl_str_mv Orozco, Javier
Roca, F. Xavier
Gonzàlez, Jordi
author Orozco, Javier
author_facet Orozco, Javier
Roca, F. Xavier
Gonzàlez, Jordi
author_role author
author2 Roca, F. Xavier
Gonzàlez, Jordi
author2_role author
author
dc.subject.none.fl_str_mv Eyelid and iris tracking
Appearance models
Blinking
Iris saccade
Real-time gaze tracking
Pattern recognition
topic Eyelid and iris tracking
Appearance models
Blinking
Iris saccade
Real-time gaze tracking
Pattern recognition
description Psychological evidence has emphasized the importance of eye gaze analysis in human computer interaction and emotion interpretation. To this end, current image analysis algorithms take into consideration eye-lid and iris motion detection using colour information and edge detectors. However, eye movement is fast and and hence difficult to use to obtain a precise and robust tracking. Instead, our method proposed to describe eyelid and iris movements as continuous variables using appearance-based tracking. This approach combines the strengths of adaptive appearance models, optimization methods and backtracking techniques. Thus, in the proposed method textures are learned on-line from near frontal images and illumination changes, occlusions and fast movements are managed. The method achieves real-time performance by combining two appearance-based trackers to a backtracking algorithm for eyelid estimation and another for iris estimation. These contributions represent a significant advance towards a reliable gaze motion description for HCI and expression analysis, where the strength of complementary methodologies are combined to avoid using high quality images, colour information, texture training, camera settings and other time-consuming processes.
publishDate 2009
dc.date.none.fl_str_mv 2009
2010
2010
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Postprint
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/30588
url http://hdl.handle.net/10261/30588
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv http://dx.doi.org/10.1007/s00138-008-0130-6
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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