@inproceedings{wood16_eccv,
title = {A 3D Morphable Eye Region Model for Gaze Estimation},
author = {Erroll Wood and Tadas Baltrusaitis and Louis-Philippe Morency and Peter Robinson and Andreas Bulling},
url = {https://perceptual.mpi-inf.mpg.de/files/2017/02/wood16_eccv.pdf

https://www.youtube.com/watch?v=n_htSvUq7iU},
doi = {10.1007/978-3-319-46448-0_18},
year = {2016},
date = {2016-07-11},
booktitle = {Proc. of the European Conference on Computer Vision (ECCV)},
pages = {297-313},
abstract = {Morphable face models are a powerful tool, but have previ- ously 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 simul- taneously. 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° in a challenging user-independent scenario.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}