自动化学报2016，Vol.42Issue(6)：883-891,9.DOI:10.16383/j.aas.2016.c150638
基于ROI-KNN卷积神经网络的面部表情识别
Facial Expression Recognition Using ROI-KNN Deep Convolutional Neural Networks
摘要
Abstract
Deep neural networks have been proved to be able to mine distributed representation of data including image, speech and text. By building two models of deep convolutional neural networks and deep sparse rectifier neural networks on facial expression dataset, we make contrastive evaluations in facial expression recognition system with deep neural networks. Additionally, combining region of interest (ROI) and K-nearest neighbors (KNN), we propose a fast and simple improved method called “ROI-KNN” for facial expression classification, which relieves the poor generalization of deep neural networks due to lacking of data and decreases the testing error rate apparently and generally. The proposed method also improves the robustness of deep learning in facial expression classification.关键词
卷积神经网络/面部情感识别/模型泛化/先验知识Key words
Convolution neural networks/facial expression recognition/model generalization/prior knowledge引用本文复制引用
孙晓,潘汀,任福继..基于ROI-KNN卷积神经网络的面部表情识别[J].自动化学报,2016,42(6):883-891,9.基金项目
国家自然科学基金重点项目(61432004),安徽省自然科学基金(1508085QF119),模式识别国家重点实验室开放课题(NLPR201407345),中国博士后科学基金(2015M580532),合肥工业大学2015年国家省级大学生创新训练计划项目(2015cxcys109)资助Supported by Key Program of National Natural Foundation Science of China (61432004), the Natural Science Foundation of Anhui Province (1508085QF119), Open Project Program of the National Laboratory of Pattern Recognition (NLPR201407345), China Postdoctoral Science Foundation (2015M580532), and Na-tional Training Program of Innovation and Entrepreneurship for HFUT Undergraduates (2015cxcys109) （61432004）
