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  1. 西安电子科技大学 电子工程学院,陕西 西安 710071
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2006-10-20 发布日期:2006-10-30

Bayesian face detection algorithm based on skin segmentation

WEN Jing;GAO Xin-bo   

  1. School of Electronic Engineering, Xidian Univ., Xi′an 710071, China
  • Received:1900-01-01 Revised:1900-01-01 Online:2006-10-20 Published:2006-10-30

摘要: 为了结合颜色信息和人脸特征构造快速高精度的人脸检测系统,提出一种基于肤色模型的贝叶斯人脸检测算法.新算法包括两大步骤,即肤色检测和人脸特征检测.前者借助混合高斯模型对人脸肤色区域建模,生成肤色检测规则.同时,针对合理选择混合高斯模型中分量数问题,提出一种基于聚类有效性函数的最优分量数确定方法,以提高肤色检测的精度.在人脸特征区域判决中引入菱形搜索,与贝叶斯判决相结合,以提高人脸特征区域的检测速度.新算法具有较高的检测精度和较低的漏警率,同时能够满足实时检测的要求.

关键词: 肤色分割, 混合高斯模型, 修正划分模糊度, 贝叶斯, 菱形搜索

Abstract: In order to build up a fast and effective system for face detection by combining the skin color information with facial features, the paper proposes a Bayesian detection algorithm based on the skin model. There are mainly two steps in our algorithm: skin color detection and facial feature detection. The former models skin regions to the Gaussian Mixture Model and sets up rules for skin detection. Meantime, a new method based on the cluster validity function is proposed to determine the optimal numbers of GMM components so as to improve the precision of detection. To speed up the facial feature detection, a diamond search algorithm is introduced in the Bayesian classifier. Experimental results illustrate the high detection precision and low false alarm of the proposed algorithm. Moreover, it can realize the face detection in real time basically.

Key words: skin segmentation, GMM, MPFD, Bayesian, diamond search


  • TP181