计算机技术与发展2016，Vol.26Issue(11)：1-4,4.DOI:10.3969/j.issn.1673-629X.2016.11.001
基于深度学习的头部姿态估计
Head Pose Estimation Based on Deep Learning
摘要
Abstract
Head pose estimation has been widely used in the field of artificial intelligence,pattern recognition and intelligent human-com-puter interaction and so on. Good head pose estimation algorithm should deal with light,noise,identity,shelter and other factors robustly, but so far how to improve the accuracy and robustness of attitude estimation remains a major challenge in the field of computer vision. A method based on deep learning for pose estimation is presented. Deep learning with a strong learning ability,it can extract high-level im-age features of the input image by through a series of non-linear operation,then classifying the input image using the extracted feature. Such characteristics have greater differences in pose,while they are robust of light,identity,occlusion and other factors. The proposed head pose estimation is evaluated on the CAS-PEAL data set. Experimental results show that this method is effective to improve the accu-racy of pose estimation.关键词
头部姿态估计/深度学习/提取特征/分类Key words
head pose estimation/deep learning/extracting feature/classification分类
信息技术与安全科学引用本文复制引用
贺飞翔,赵启军..基于深度学习的头部姿态估计[J].计算机技术与发展,2016,26(11):1-4,4.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）
