南京大学学报（自然科学版）2013，Vol.49Issue(2)：183-188,6.
一种自动的人脸轮廓定位方法
An automatic face contour extracting method
摘要
Abstract
Images containing faces are essential to intelligent vision-based human computer interaction,and research efforts in face processing include face recognition, face tracking, and expression recognition. Many applications assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. However,such a problem is challenging because faces are non-rigid and have a high degree of variability in size,shape,color,and texture. The purpose of this paper is to provide a relative robust method for face segmentation in images based on curve evolution methodology. Since the face image always has a blur boundary and little gradient changes,the region segmentations obtained by the original Chan-Vese model are generally unsatisfactory and need large amount of calculations. To achieve more accurate facial contour extraction and face segmentation, a new face segmentation scheme based on curve evolution model is proposed which is a combination of Chan-Vese model, sparse-field algorithm, face detection and mathematical morphology operators. Experimental results show that the improved algorithm can effectively detect the local blur and breaking boundaries on the face images without any fractures in the curve,hence resulting in favorable face segmentations.关键词
人脸分割/人脸轮廓提取/无边缘几何活动轮廓模型/水平集/稀疏场算法Key words
face segmentation/face contour extraction/Chan-Vese model/level set/sparse-field引用本文复制引用
李昕昕,龚勋,夏冉..一种自动的人脸轮廓定位方法[J].南京大学学报（自然科学版）,2013,49(2):183-188,6.基金项目
国家自然科学基金(61202191),中央高校基本科研业务费专项资金(SWJTU12CX095) （61202191）
