基于深度网络的人脸区域分割方法  

Face Region Segmentation Method Based on Deep Network

作　　者：杜星悦 董洪伟[1] 杨振 DU Xingyue;DONG Hongwei;YANG Zhen(College of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China)

机构地区：[1]江南大学物联网工程学院,江苏无锡214122

出　　处：《计算机工程与应用》2019年第8期171-174,共4页Computer Engineering and Applications

摘　　要：语义分割是近年来比较热的一个主题,而其中对二维人脸图片的区域分割技术的研究,对机器人应用,人脸头部姿势预测,三维人脸识别,分割,动画等方面有重要促进意义。由于目前的人脸区域分割算法在精度上存在一定不足,提出了基于深度网络的人脸区域分割方法,并进行了实验。实验结果表明该算法相较于以前的一些方法精度更高,鲁棒性好,有实际应用意义。Semantic segmentation is a popular theme in recent years. The two-dimensional face image segmentation technology is important for the field of robot industry, the head pose prediction, three-dimensional face recognition, face seg-mentation, facial animation and other fields. Because of the shortage of the existing segmentation algorithm, it proposes a face region segmentation method based on deep network. The experimental results show that the algorithm is of high precision and good robustness, which has practical application significance.

关 键 词：语义分割 二维人脸 区域分割 深度网络 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]