Paper Info
Title
A 3d Morphable Eye Region Model For Gaze Estimation
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 degrees in a challenging user-independent scenario.
Year
DOI
Venue
2016
10.1007/978-3-319-46448-0_18
COMPUTER VISION - ECCV 2016, PT I
Keywords
Field
DocType
Morphable model, Gaze estimation, Analysis-by-synthesis
Computer vision,Speech coding,Gaze,Computer science,Rgb image,Artificial intelligence
Conference
Volume
ISSN
Citations 
9905
0302-9743
20
PageRank 
References 
Authors
0.63
26
5
Name
Order
Citations
PageRank
Erroll Wood1591.86
Tadas Baltrusaitis2200.63
Louis-Philippe Morency33220200.79
Peter Robinson41438129.42
Andreas Bulling52279133.41