On improving eye feature extraction using deformable templates

摘要

An improved method of extracting eye features from facial images using eye templates is described. It retains all advantages of the deformable template method originally proposed by A. L. Yuille, P. W. Hallinan and D. S. Cohen (Int. J. Comput. Vision 99–111 (1989)) and rectifies some of its weaknesses. This is achieved by the following modifications. First, the original eye template and the overall energy function to represent the most salient features of the eye are modified. Secondly, in order to simplify the issue of selecting weights for the energy terms, the value of each energy term is normalized in the range 0–1 and only two different weights are assigned. This weighting schedule does not require expert knowledge therefore it is more user friendly. Thirdly, all parameters of the template are changed simultaneously during the minimization process rather than using a sequential procedure. This scheme prevents some parameters of the eye template from being overly changed, helps the algorithm to converge to the global minimum, and reduces the processing time. The selection of initial parameters of the eye template is based on an eye window obtained in preprocessing. Experimental results are presented to demonstrate the efficacy of the algorithm. A comparison study of various processing schemes is also given.