Facial and eye gaze detection

Kang Ryoung Park; Jeong Jun Lee; Jaihie Kim

doi:10.1007/3-540-36181-2_37

Facial and eye gaze detection

Kang Ryoung Park, Jeong Jun Lee, Jaihie Kim

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

18 Citations (Scopus)

Abstract

Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye’s movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.8 cm of RMS error.

Original language	English
Title of host publication	Biologically Motivated Computer Vision - 2nd International Workshop, BMCV 2002, Proceedings
Editors	Heinrich H. Bulthoff, Christian Wallraven, Seong-Whan Lee, Tomaso A. Poggio
Publisher	Springer Verlag
Pages	368-376
Number of pages	9
ISBN (Electronic)	9783540001744
DOIs	https://doi.org/10.1007/3-540-36181-2_37
Publication status	Published - 2002
Event	2nd International Workshop on Biologically Motivated Computer Vision, BMCV 2002 - Tubingen, Germany Duration: 2002 Nov 22 → 2002 Nov 24

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2525
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	2nd International Workshop on Biologically Motivated Computer Vision, BMCV 2002
Country/Territory	Germany
City	Tubingen
Period	02/11/22 → 02/11/24

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2002.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/3-540-36181-2_37

Cite this

Park, K. R., Lee, J. J., & Kim, J. (2002). Facial and eye gaze detection. In H. H. Bulthoff, C. Wallraven, S-W. Lee, & T. A. Poggio (Eds.), Biologically Motivated Computer Vision - 2nd International Workshop, BMCV 2002, Proceedings (pp. 368-376). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2525). Springer Verlag. https://doi.org/10.1007/3-540-36181-2_37

Park, Kang Ryoung ; Lee, Jeong Jun ; Kim, Jaihie. / Facial and eye gaze detection. Biologically Motivated Computer Vision - 2nd International Workshop, BMCV 2002, Proceedings. editor / Heinrich H. Bulthoff ; Christian Wallraven ; Seong-Whan Lee ; Tomaso A. Poggio. Springer Verlag, 2002. pp. 368-376 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye{\textquoteright}s movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.8 cm of RMS error.",

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Park, KR, Lee, JJ & Kim, J 2002, Facial and eye gaze detection. in HH Bulthoff, C Wallraven, S-W Lee & TA Poggio (eds), Biologically Motivated Computer Vision - 2nd International Workshop, BMCV 2002, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2525, Springer Verlag, pp. 368-376, 2nd International Workshop on Biologically Motivated Computer Vision, BMCV 2002, Tubingen, Germany, 02/11/22. https://doi.org/10.1007/3-540-36181-2_37

Facial and eye gaze detection. / Park, Kang Ryoung; Lee, Jeong Jun; Kim, Jaihie.

Biologically Motivated Computer Vision - 2nd International Workshop, BMCV 2002, Proceedings. ed. / Heinrich H. Bulthoff; Christian Wallraven; Seong-Whan Lee; Tomaso A. Poggio. Springer Verlag, 2002. p. 368-376 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2525).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Lee, Jeong Jun

AU - Kim, Jaihie

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PY - 2002

Y1 - 2002

N2 - Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye’s movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.8 cm of RMS error.

AB - Gaze detection is to locate the position on a monitor screen where a user is looking. In our work, we implement it with a computer vision system setting a IR-LED based single camera. To detect the gaze position, we locate facial features, which is effectively performed with IR-LED based camera and SVM(Support Vector Machine). When a user gazes at a position of monitor, we can compute the 3D positions of those features based on 3D rotation and translation estimation and affine transform. Finally, the gaze position by the facial movements is computed from the normal vector of the plane determined by those computed 3D positions of features. In addition, we use a trained neural network to detect the gaze position by eye’s movement. As experimental results, we can obtain the facial and eye gaze position on a monitor and the gaze position accuracy between the computed positions and the real ones is about 4.8 cm of RMS error.

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Park KR, Lee JJ, Kim J. Facial and eye gaze detection. In Bulthoff HH, Wallraven C, Lee S-W, Poggio TA, editors, Biologically Motivated Computer Vision - 2nd International Workshop, BMCV 2002, Proceedings. Springer Verlag. 2002. p. 368-376. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/3-540-36181-2_37

Facial and eye gaze detection

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All Science Journal Classification (ASJC) codes

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