Article

A fast and robust 3D head pose and gaze estimation system

Authors:

Koichi Kinoshita,

Yong Ma,

Shihong Lao,

Masato KawaadeAuthors Info & Claims

ICMI '06: Proceedings of the 8th international conference on Multimodal interfaces

Pages 137 - 138

https://doi.org/10.1145/1180995.1181026

Published: 02 November 2006 Publication History

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Abstract

We developed a fast and robust head pose and gaze estimation system. This system can detect facial points and estimate 3D pose angles and gaze direction under various conditions including facial expression changes and partial occlusion. We need only one face image as input and do not need special devices such as blinking LEDs or stereo cameras. Moreover, no calibration is needed. The system shows a 95% head pose estimation accuracy and 81% gaze estimation accuracy (when the error margin is 15 degrees). The processing time is about 15 ms/frame (Pentium4 3.2 GHz). Acceptable range of facial pose is within a yaw (left-right) of ±60 degrees and within a pitch (up-down) of ±30 degrees.

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Yamashita, T., et al. Fast Omni Directional Face Detection System. Demo program of Int. Conf. Computer Vision, 2005.

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Huang, C., et al. Omni-Directional Face Detection based on Real AdaBoost. In Proceedings of ICIP, 2004.

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Cited By

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Sigal LIsard MHaussecker HBlack M(2012)Loose-limbed PeopleInternational Journal of Computer Vision10.1007/s11263-011-0493-498:1(15-48)Online publication date: 1-May-2012
https://dl.acm.org/doi/10.1007/s11263-011-0493-4
Lee KKim DHong K(2011)An implementation of SVM-based gaze recognition system using advanced eye region detectionProceedings of the 2011 international conference on Computational science and Its applications - Volume Part V10.5555/2029427.2029434(58-69)Online publication date: 20-Jun-2011
https://dl.acm.org/doi/10.5555/2029427.2029434
Lee KKim DHong K(2011)An Implementation of SVM-Based Gaze Recognition System Using Advanced Eye Region DetectionComputational Science and Its Applications - ICCSA 201110.1007/978-3-642-21934-4_6(58-69)Online publication date: 2011
https://doi.org/10.1007/978-3-642-21934-4_6
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Index Terms

A fast and robust 3D head pose and gaze estimation system
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Tracking
      2. Computer vision tasks
        Scene understanding

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Published In

ICMI '06: Proceedings of the 8th international conference on Multimodal interfaces

November 2006

404 pages

ISBN:159593541X

DOI:10.1145/1180995

General Chairs:
Francis Quek
Virginia Tech, USA
,
Jie Yang
Carnegie Mellon University, USA
,
Program Chairs:
Dominic Massaro
University of California, Santa Cruz, USA
,
Abeer Alwan
University of California, Los Angeles, USA
,
Timothy J. Hazen
Massachusetts Institute of Technology, USA

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Association for Computing Machinery

New York, NY, United States

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Published: 02 November 2006

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ICMI06: 8th International Conference on Multimodal Interfaces 2006

November 2 - 4, 2006

Alberta, Banff, Canada

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Overall Acceptance Rate 453 of 1,080 submissions, 42%

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Sigal LIsard MHaussecker HBlack M(2012)Loose-limbed PeopleInternational Journal of Computer Vision10.1007/s11263-011-0493-498:1(15-48)Online publication date: 1-May-2012
https://dl.acm.org/doi/10.1007/s11263-011-0493-4
Lee KKim DHong K(2011)An implementation of SVM-based gaze recognition system using advanced eye region detectionProceedings of the 2011 international conference on Computational science and Its applications - Volume Part V10.5555/2029427.2029434(58-69)Online publication date: 20-Jun-2011
https://dl.acm.org/doi/10.5555/2029427.2029434
Lee KKim DHong K(2011)An Implementation of SVM-Based Gaze Recognition System Using Advanced Eye Region DetectionComputational Science and Its Applications - ICCSA 201110.1007/978-3-642-21934-4_6(58-69)Online publication date: 2011
https://doi.org/10.1007/978-3-642-21934-4_6
Lee KKim DHong K(2010)An Implementation of Gaze Recognition System Based on SVMThe KIPS Transactions:PartB10.3745/KIPSTB.2010.17B.1.00117B:1(1-8)Online publication date: 28-Feb-2010
https://doi.org/10.3745/KIPSTB.2010.17B.1.001
Stommel MHerzog O(2010)Learning of face components in coherent and disturbed constellations2010 25th International Conference of Image and Vision Computing New Zealand10.1109/IVCNZ.2010.6148832(1-8)Online publication date: Nov-2010
https://doi.org/10.1109/IVCNZ.2010.6148832
Ptucha RSavakis A(2009)Facial pose estimation using a symmetrical feature modelProceedings of the 2009 IEEE international conference on Multimedia and Expo10.5555/1698924.1699344(1664-1667)Online publication date: 28-Jun-2009
https://dl.acm.org/doi/10.5555/1698924.1699344
Ptucha RSavakis A(2009)Facial pose estimation using a symmetrical feature model2009 IEEE International Conference on Multimedia and Expo10.1109/ICME.2009.5202840(1664-1667)Online publication date: Jun-2009
https://doi.org/10.1109/ICME.2009.5202840
Wang HPan CChaillou C(2009)Tracking eye gaze under coordinated head rotations with an ordinary cameraProceedings of the 9th Asian conference on Computer Vision - Volume Part II10.1007/978-3-642-12304-7_12(120-129)Online publication date: 23-Sep-2009
https://dl.acm.org/doi/10.1007/978-3-642-12304-7_12

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Learning gaze biases with head motion for head pose-free gaze estimation

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