Computer Engineering and Applications ›› 2019, Vol. 55 ›› Issue (8): 171-174.DOI: 10.3778/j.issn.1002-8331.1801-0055

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Face Region Segmentation Method Based on Deep Network

DU Xingyue, DONG Hongwei, YANG Zhen   

  1. College of Internet of Things Engineering, Jiangnan University, Wuxi, Jiangsu 214122, China
  • Online:2019-04-15 Published:2019-04-15


杜星悦,董洪伟,杨  振   

  1. 江南大学 物联网工程学院,江苏 无锡 214122

Abstract: 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 segmentation, 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.

Key words: semantic segmentation, two dimensional face, region segmentation, deep network

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。

关键词: 语义分割, 二维人脸, 区域分割, 深度网络