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∘ in a challenging user-independent scenario.
%0 Conference Paper
%1 wood16_eccv
%A Wood, Erroll
%A Baltrusaitis, Tadas
%A Morency, Louis-Philippe
%A Robinson, Peter
%A Bulling, Andreas
%B Proceedings of the European Conference on Computer Vision (ECCV)
%D 2016
%K 2016 A07 sfbtrr161 visus:bullinas
%P 297-313
%R 10.1007/978-3-319-46448-0_18
%T A 3D Morphable Eye Region Model for Gaze Estimation
%U https://link.springer.com/chapter/10.1007%2F978-3-319-46448-0_18
%X 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∘ in a challenging user-independent scenario.
@inproceedings{wood16_eccv,
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∘ in a challenging user-independent scenario.},
added-at = {2020-02-28T13:29:01.000+0100},
author = {Wood, Erroll and Baltrusaitis, Tadas and Morency, Louis-Philippe and Robinson, Peter and Bulling, Andreas},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/28d9dd7abf4087243b01b8cbfd8c518b5/leonkokkoliadis},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
doi = {10.1007/978-3-319-46448-0_18},
interhash = {9ad824871c47083e79aec51cccf9c396},
intrahash = {8d9dd7abf4087243b01b8cbfd8c518b5},
keywords = {2016 A07 sfbtrr161 visus:bullinas},
pages = {297-313},
timestamp = {2020-02-28T12:30:28.000+0100},
title = {A 3D Morphable Eye Region Model for Gaze Estimation},
url = {https://link.springer.com/chapter/10.1007%2F978-3-319-46448-0_18},
year = 2016
}
