Mathematical Sciences: Feature Detection and Representation of Faces Using Deformable Templates

这项为期一年的资助将允许Yuille博士和一名学生扩展他们在人脸表征和视觉识别方面的初步工作。他们目前的系统可以通过使用可变形模板的参数适应来定位眼睛和嘴巴等强特征。他们现在正在应用强大的统计方法来识别部分遮挡或未解决的特征，并且还将研究金字塔算法来匹配全局人脸模板。目标是在存在噪声和干扰的情况下实现强大的人脸识别。

This one-year grant will permit Dr. Yuille and one student to extend their preliminary work in representation and visual recognition of human faces. Their current system can locate strong features such as eyes and mouths by using parametric adaptation of deformable templates. They are now applying robust statistical methods to identification of partially occluded or unresolved features, and will also study pyramid algorithms for matching a global face template. The goal is robust face recognition in the presence of noise and distractions.