基于深度图像的人脸模型特征点自动标定  

Automatic Location of Feature Points on Three-dimensional Facial Model Based on Depth Image

作　　者：李康[1] 尚鹏[1] 耿国华[1] 

机构地区：[1]西北大学信息科学与技术学院,西安710127

出　　处：《计算机科学》2014年第4期287-291,共5页Computer Science

基　　金：973计划前期研究专项课题:文化遗产数字化生存中的表示与复原理论方法研究(2011CB311802);国家自然科学基金重点项目:颅面形态学和颅面重构的研究(60736008);国家自然科学基金面上项目:自动颅像重合身份认证关键技术研究(61172170)资助

摘　　要：准确标定人脸三维模型上的特征点是颅面形态学研究的关键问题之一。针对目前人脸特征点标定需要手工干预等问题,提出了一种基于深度图像的人脸三维模型特征点标定方法,该方法首先生成人脸三维模型的二维深度图像,然后采用SUSAN算子、灰度积分投影等方法在该图像上标定特征点,最终将标定好的特征点映射到人脸三维模型上,从而实现鼻尖点、嘴角点、眼角点以及耳朵处13个特征点的标定。实验结果表明,该方法可自动标定人脸模型特征点,准确获得特征点的位置,有效解决了人脸特征点标定因人工参与而带来的不准确性。Accurate location of feature points on the three-dimensional facial model is one of the key issues in the craniofacial morphological research.For manual intervention in the process of facial feature points,the paper proposed the method based on the depth image of 3D facial model to locate the feature points.First of all,it generates the two-dimensional depth image of three-dimensional facial model,and then uses SUSAN operator,gray-level integral projection method to locate the feature points on this image,and ultimately mas the located feature points to the facial model,thereby achieves location of thirteen points including nose tip point,mouth corner points,eye comer point and ears points.Experimental results show that the method can automatically locate feature points of the facial model,and accurately obtain the position of the feature points,and effectively solve the problem caused by human involvement of the facial feature point location.

关 键 词：人脸三维模型 特征点标定 二维深度图像 SUSAN算子 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]