控制理论与应用2017，Vol.34Issue(9)：1236-1243,8.DOI:10.7641/CTA.2017.70072
融合人脸五官信息的深度年龄估计
Deep age estimation by fusing facial information
摘要
Abstract
The paper presents a new mode of solution for deep age estimation by facial features auxiliary,which fuses the traditional facial information with the convolutional neural network(CNN)to achieve the age estimation,in order to reinforce the generalization ability of system model. The solution estimates age from image pixels directly,which makes the locally aligned face image block generated by the key points of the face as the input of the CNN.The system improves the performance significantly by using the multi-scale CNN network structure. At the same time,it apply the traditional method to strengthen the information of facial areas. The experiments on MORPH AlbumⅡillustrate the superiorities of the proposed method over other state-of-the-art methods.关键词
年龄估计/五官辅助/卷积神经网络/多尺度/多任务Key words
age estimation/facial features auxiliary/convolutional neural network/multi-scale/multi-task分类
信息技术与安全科学引用本文复制引用
李云飞,卢朝阳,李静..融合人脸五官信息的深度年龄估计[J].控制理论与应用,2017,34(9):1236-1243,8.基金项目
国家自然科学基金项目(61502364),渭南师范学院科研基金项目(16YKS001)资助.Supported by National Natural Science Foundation of China(61502364)and Scientific Research Foundation of Weinan Normal University(16YKS 001). （61502364）
