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Vision-Based Facial and Eye Gaze Tracking System

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KI 2004: Advances in Artificial Intelligence (KI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3238))

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Abstract

Gaze detection is to locate the position (on a monitor) where a user is looking. Previous researches use one wide view camera, which can capture a whole user’s face. However, the image resolution is too low with such a camera and the fine movements of user’s eye cannot be exactly detected. So, we propose the new gaze detection system with dual cameras (a wide and a narrow view camera). In order to locate the user’s eye position accurately, the narrow-view camera has the functionalities of auto focusing/panning/tilting based on the detected 3D eye positions from the wide view camera. In addition, we use the IR-LED illuminators for wide and narrow view camera, which can ease the detecting of facial features, pupil and iris position. To overcome the problem of specular reflection on glasses by illuminator, we use dual IR-LED illuminators for wide and narrow view camera and detect the accurate eye position, which is not hidden by the specular reflection. Experimental results show that the gaze detection error between the computed positions and the real ones is about 2.89 cm of RMS error.

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Author information

Authors and Affiliations

  1. Division of Media Technology, SangMyung University, 7 Hongji-Dong, JongRo-Gu, Seoul, Republic of Korea

    Kang Ryoung Park

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  1. Kang Ryoung Park
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Editor information

Editors and Affiliations

  1. Institute for Artificial Intelligence, Ulm University, Germany

    Susanne Biundo

  2. Fakultät für Ingenieurwissenschaften und Informatik, Universität Ulm, 89069, Ulm, v

    Thom Frühwirth

  3. Institute of Neural Information Processing, University of Ulm, D-89069, Ulm, Germany

    Günther Palm

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© 2004 Springer-Verlag Berlin Heidelberg

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Park, K.R. (2004). Vision-Based Facial and Eye Gaze Tracking System. In: Biundo, S., Frühwirth, T., Palm, G. (eds) KI 2004: Advances in Artificial Intelligence. KI 2004. Lecture Notes in Computer Science(), vol 3238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30221-6_34

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  • DOI: https://doi.org/10.1007/978-3-540-30221-6_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23166-0

  • Online ISBN: 978-3-540-30221-6

  • eBook Packages: Springer Book Archive

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