计算机技术与发展2016，Vol.26Issue(7)：11-13,18,4.DOI:10.3969/j.issn.1673-629X.2016.07.003
基于深度学习的人脸姿态分类方法
Face Pose Classification Method Based on Deep Learning
摘要
Abstract
Face pose usually contains useful information,so detecting it accurately plays an important role in face alignment,human be-havior analysis and drivers' fatigue driving monitoring. A novel method is proposed in this paper which applies deep learning to human face pose classification based on convolutional neural networks. It can be divided into two steps mainly. First,layer one classifies pose into 5 categories at direction yaw,and it's of robustness at direction roll. Then layer two takes the result of step one as input to classify pose into 3 categories at direction pitch. All outputs are robust to illumination. The cascade connection is used to test on public benchmark,and the result shows that its accuracy is 95%. In real surveillance video,it has both high accuracy and fast estimating speed. Due to the partic-ularity of experiment,it only contrasts the result to itself. Experimental results show that well-designed cascade connection of neural net-work can estimate pose well.关键词
姿态分类/级联/深度学习/卷积神经网络Key words
pose classification/cascade/deep learning/convolutional neural network分类
信息技术与安全科学引用本文复制引用
邓宗平,赵启军,陈虎..基于深度学习的人脸姿态分类方法[J].计算机技术与发展,2016,26(7):11-13,18,4.基金项目
国家自然科学基金资助项目(61202160,61202161) （61202160,61202161）
科技部重大仪器专项(2013YQ49087904) （2013YQ49087904）
