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A 3D Morphable Eye Region Model for Gaze Estimation

  • Erroll Wood
  • Tadas Baltrušaitis
  • Louis-Philippe Morency
  • Peter Robinson
  • Andreas Bulling
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9905)

Abstract

Morphable face models are a powerful tool, but have previously failed to model the eye accurately due to complexities in its material and motion. We present a new multi-part model of the eye that includes a morphable model of the facial eye region, as well as an anatomy-based eyeball model. It is the first morphable model that accurately captures eye region shape, since it was built from high-quality head scans. It is also the first to allow independent eyeball movement, since we treat it as a separate part. To showcase our model we present a new method for illumination- and head-pose–invariant gaze estimation from a single RGB image. We fit our model to an image through analysis-by-synthesis, solving for eye region shape, texture, eyeball pose, and illumination simultaneously. The fitted eyeball pose parameters are then used to estimate gaze direction. Through evaluation on two standard datasets we show that our method generalizes to both webcam and high-quality camera images, and outperforms a state-of-the-art CNN method achieving a gaze estimation accuracy of \(9.44^\circ \) in a challenging user-independent scenario.

Keywords

Morphable model Gaze estimation Analysis-by-synthesis 

Supplementary material

Supplementary material 1 (mp4 18664 KB)

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Erroll Wood
    • 1
  • Tadas Baltrušaitis
    • 2
  • Louis-Philippe Morency
    • 2
  • Peter Robinson
    • 1
  • Andreas Bulling
    • 3
  1. 1.University of CambridgeCambridgeUK
  2. 2.Carnegie Mellon UniversityPittsburghUSA
  3. 3.Max Planck Institute for InformaticsSaarbrückenGermany

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