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Eyes Segmentation Applied to Gaze Direction and Vigilance Estimation

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3687))

Abstract

An efficient algorithm to iris segmentation and its application to automatic and non-intrusive gaze tracking and vigilance estimation is presented and discussed. A luminance gradient technique is used to fit the irises from face images. A robust preprocessing which mimics the human retina is used in such a way that a robust system to luminance variations is obtained and contrast enhancement is achieved. The validation of the proposed algorithm is experimentally demonstrated by using three well-known test databases: the FERET database, the Yale database and the Cohn-Kanade database. Experimental results confirm the effectiveness and the robustness of the proposed approach to be applied successfully in gaze direction and vigilance estimation.

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References

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© 2005 Springer-Verlag Berlin Heidelberg

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Hammal, Z., Massot, C., Bedoya, G., Caplier, A. (2005). Eyes Segmentation Applied to Gaze Direction and Vigilance Estimation. In: Singh, S., Singh, M., Apte, C., Perner, P. (eds) Pattern Recognition and Image Analysis. ICAPR 2005. Lecture Notes in Computer Science, vol 3687. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552499_27

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  • DOI: https://doi.org/10.1007/11552499_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28833-6

  • Online ISBN: 978-3-540-31999-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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