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3D Gaze tracking by combining eye- and facial-gaze vectors

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Abstract

We propose a 3D gaze-tracking method that combines accurate 3D eye- and facial-gaze vectors estimated from a Kinect v2 high-definition face model. Using accurate 3D facial and ocular feature positions, gaze positions can be calculated more accurately than with previous methods. Considering the image resolution of the face and eye regions, two gaze vectors are combined as a weighted sum, allocating more weight to facial-gaze vectors. Hence, the facial orientation mainly determines the gaze position, and eye-gaze vectors then perform minor manipulations. The 3D facial-gaze vector is first defined, and the 3D rotational center of the eyeball is then estimated; together, these define the 3D eye-gaze vector. Finally, the intersection point between the 3D gaze vector and the physical display plane is calculated as the gaze position. Experimental results show that the average gaze estimation root-mean-square error was approximately 23 pixels from the desired position at a resolution of \(1920\times 1080\).

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Acknowledgments

This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2016-H8501-16-1014), (IITP-2016-R0992-16-1014) supervised by the IITP (Institute for Information & communications Technology Promotion).

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Authors and Affiliations

  1. Department of Computer Science, Graduate School, Sangmyung University, Seoul, Republic of Korea

    Byoung Cheul Kim, Daejune Ko & Unsoo Jang

  2. Department of Computer Science, Sangmyung University, Seoul, Republic of Korea

    Hyuksoo Han & Eui Chul Lee

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  1. Byoung Cheul Kim
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  2. Daejune Ko
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Correspondence to Eui Chul Lee.

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Kim, B.C., Ko, D., Jang, U. et al. 3D Gaze tracking by combining eye- and facial-gaze vectors. J Supercomput 73, 3038–3052 (2017). https://doi.org/10.1007/s11227-016-1817-5

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  • DOI: https://doi.org/10.1007/s11227-016-1817-5

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