The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

Most eye trackers work well for open eyes. However blinking is a physiological necessity for humans. More over, for applications such as facial expression analysis and driver awareness systems, we need to do more than tracking of the locations of the person's eyes but obtain their detailed description. We need to recover the state of the eyes (i.e., whether they are open or closed), and the parameters of an eye model (e.g., the location and radius of the iris, and the corners and height of the eye opening). We develop a dual-state model-based system for tracking eye features that uses convergent tracking techniques and show how it can be used to detect whether the eyes are open or closed, and to recover the parameters of the eye model. Processing speed on a Pentium II 400 MHz PC is approximately 3 frames/second. In experimental tests on 500 image sequences from child and adult subjects with varying colors of skin and eye, accurate tracking results are obtained in 98% of image sequences.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): Face Group and Component Analysis

Associated Project(s): Facial Expression Analysis and Face Databases

Text Reference

Ying-Li Tian, Takeo Kanade, and Jeffrey Cohn, "Dual-state Parametric Eye Tracking," Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), March, 2000, pp. 110 - 115.

BibTeX Reference

@inproceedings{Tian_2000_3251,
   author = "Ying-Li Tian and Takeo Kanade and Jeffrey Cohn",
   title = "Dual-state Parametric Eye Tracking",
   booktitle = "Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG'00)",
   pages = "110 - 115",
   month = "March",
   year = "2000",
}

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