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Robust gaze estimation via normalized iris center-eye corner vector

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

Gaze estimation plays an important role in many practical scenarios such as human robot interaction. Although high accurate gaze estimation could be obtained in constrained settings with additional IR sources or depth sensors, single web-cam based gaze estimation still remains challenging. This paper propose a normalized iris center-eye corner (NIC-EC) vector based gaze estimation methods using a single, low cost web-cam. Firstly, reliable facial features and pupil centers are extracted. Then, the NIC-EC vector is proposed to enhance the robustness and accuracy for pupil center-eye corner vector based gaze estimations. Finally, an interpolation method is employed for the mapping between constructed vectors and points of regard. Experimental results showed that the proposed method has significantly improved the accuracy over the pupil center-eye corner vector based gaze estimation method with average accuracy of 1.66∘ under slight head movements.
Original languageEnglish
Title of host publicationIntelligent Robotics and Applications
Subtitle of host publication9th International Conference, ICIRA 2016, Tokyo, Japan, August 22-24, 2016, Proceedings, Part I
EditorsNaoyuki Kubota, Kazuo Kiguchi, Honghai Liu, Takenori Obo
PublisherSpringer
Pages300-309
DOIs
Publication statusPublished - 3 Aug 2016
EventInternational Conference on Intelligent Robotics and Applications 2016 - Tokyo Metropolitan University, Tokyo, Japan
Duration: 20 Aug 201625 Aug 2016
http://www.comp.sd.tmu.ac.jp/icira2016/

Publication series

NameLecture Notes in Computer Science
Volume9834
ISSN (Print)0302-9743

Conference

ConferenceInternational Conference on Intelligent Robotics and Applications 2016
Abbreviated titleICIRA2016
CountryJapan
CityTokyo
Period20/08/1625/08/16
Internet address

Documents

  • Robust Gaze ICIRA2016

    Rights statement: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-43506-0_26.

    Accepted author manuscript (Post-print), 391 KB, PDF document

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