A new method of detecting human eyelids based on deformable templates

Abstract

In this paper, a new method of automatically detecting human eyelids using deformable templates is proposed. Deformable templates are often used in eye's feature detection although there are several drawbacks such as high computational complexity, unexpected shrinking of the templates and rotation of the template. Based on the analysis on these problems, an improved template for eyelid edge detection with several new ideas is presented. The problems of unexpected shrinking of templates and the rotations of template are overcome by using a new kind of potential field and accurate estimations of the template parameters. Dynamic threshold selection and eye corner field are adopted for better performance of eyelid edge detection and two kinds of new energy terms are used to control the eyelid template optimization. Experiments show that the eyelid template and the optimization method are effective even for complex changes in facial images, such as eye opening and closing, obvious irises movements and rotations of heads in small angles.