Statistically Learned Deformable Eye Models

摘要

In this paper we study the feasibility of using standard deformable model fitting techniques to accurately track the deformation and motion of the human eye. To this end, we propose two highly detailed shape annotation schemes (open and close eyes), with +30 feature landmark points, high resolution eye images. We build extremely detailed Active Appearance Models (AAM), Constrained Local Models (CLM) and Supervised Descent Method (SDM) models of the human eye and report preliminary experiments comparing the relative performance of the previous techniques on the problem of eye alignment.