一种新的基于单视图的多姿态人脸识别方法  

A novel method for recognition of pose invariant face with single image

作　　者：赵明华[1] 莫瑞阳 石争浩[1] 张飞飞[1] 

机构地区：[1]西安理工大学计算机科学与工程学院,陕西西安710048

出　　处：《西安理工大学学报》2017年第1期18-23,共6页Journal of Xi'an University of Technology

基　　金：国家自然科学基金资助项目(61401355;61502382);陕西省教育厅重点实验室资助项目(14JS072);西安市碑林区科技计划资助项目(GX1621)

摘　　要：姿态变化和单视图是二维人脸识别研究的瓶颈问题。本文基于姿态矫正的思想,提出了一种基于单视图的多姿态人脸识别方法。首先,通过多视角主动表观模型进行人脸对齐和归一化;其次,基于线性回归算法寻求正、侧人脸之间的关系,并利用此关系进行姿态矫正得到正脸图像;最后,采用遗传算法筛选支持向量机的参数,并利用支持向量机对矫正后的人脸进行分类。在CASPEAL-R1人脸数据库上的实验结果表明,该方法在处理姿态变化的人脸识别问题时,对于姿态为15°、30°和45°的识别率分别达到了98%、84%和76%,识别性能高于其它方法。The pose variation and single view is a bottleneck problem for recognition of two-dimensional face.A novel method for recognition of pose-invariant face with single image based on the pose correction is proposed in this paper.Firstly,facial feature points are located based on the view-based AAM（Active Appearance Model）and face images are aligned and normalized.Secondly,mapping from the non-frontal image to the frontal image is constructed based on the algorithm for linear regression and frontal faces are obtained from non-frontal faces with different poses.Finally,the SVM（Support Vector Machine）is used to classify the facial features and the parameters of SVM is determined by the genetic algorithm.Experimental results based on the CAS-PEAL-R1 face database show that performance of the proposed approach is better than those by other approaches for pose-invariant face recognition.The recognition rates for face images with pose of 15°,30°and 45°can reach 98%,84% and 76% respectively.

关 键 词：多姿态人脸识别 线性回归 支持向量机 多视角主动表观模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]