Interpreting face images using Active Appearance Models

被引：257

作者：

Edwards, GJ ^{[1
]}

Taylor, CJ ^{[1
]}

Cootes, TF ^{[1
]}

机构：

[1] Univ Manchester, Dept Med Biophys, Wolfson Image Anal Unit, Manchester M13 9PT, Lancs, England

来源：

AUTOMATIC FACE AND GESTURE RECOGNITION - THIRD IEEE INTERNATIONAL CONFERENCE PROCEEDINGS | 1998年

关键词：

D O I：

10.1109/AFGR.1998.670965

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We demonstrate a fast, robust method of interpreting face images using an Active Appearance Model (AAM). An AAM contains a statistical model of shape and grey-level appearance which can generalise to almost any face. Matching to an image involves finding model parameters which minimise the difference between the image and a synthesised face. We observe that displacing each model parameter from the correct value induces a particular pattern in the residuals. In a training phase, the AA learns a linear model of the correlation between parameter displacements and the induced residuals. During search it measures the residuals and uses this model to correct the current parameters, leading to a better fit. A good overall match is obtained in a few iterations, even from poor starting estimates. We describe the technique in detail and show it matching to new face images.

引用

页码：300 / 305

页数：2