中国计量大学学报2017，Vol.28Issue(4)：509-515,7.DOI:10.3969/j.issn.2096-2835.2017.04.017
深度学习的视频监控下的人脸清晰度评价
Sharpness assessment based on deep learning for face images in video surveillance
摘要
Abstract
Face recognition technology has been widely used in daily life.As one of the key technologies,face sharpness evaluation got much attention.However,there were less effectiveness and robustness in using traditional methods with manual features designed.We studied a method to construct and select features by convolutional neural networks,which could improve the accuracy of face recognition.Meanwhile,the structure of double convolution layers was proposed to solve the problems such as complicated network calculation,too many parameters and much calculation time consumed.Experiments demonstrated that the face sharpness evaluation algorithm had a better accuracy and a fast processing speed.关键词
深度学习/清晰度评价/图像分类/视频监控Key words
deep learning/sharpness assessment/image classification/video surveillance分类
信息技术与安全科学引用本文复制引用
陈奇,章东平,杨力..深度学习的视频监控下的人脸清晰度评价[J].中国计量大学学报,2017,28(4):509-515,7.基金项目
浙江省自然科学基金资助项目(No.LY15F020021),浙江省科技厅公益性项目(No.2016C31079). （No.LY15F020021）
