Video Based Emotion Recognition Using CNN and BRNN

摘要：

　　Video-based Emotion recognition is a rather challenging computer vision task.It not only needs to model spatial information of each image frame,but also requires considering temporal contextual correlations among sequential frames.For this purpose,we propose a hierarchical deep network architecture to extract high-level spatial-temporal features.In this architecture,two classic deep neural networks,convolutional neutral networks(CNN)and bi-directional recurrent neutral networks(BRNN),are employed to respectively capture facial textural characteristics in spatial domain and dynamic emotion changes in temporal domain.We endeavor to coordinate the two networks by optimizing each of them,so as to boost the performance of the emotion recognition.In the challenging competition,our method achieves a promising performance compared with the baselines.

关键词： Convolutional neutral networks (CNN) Bi-directional recurrent neutral networks (BRNN) Emotion recognition

作者: Youyi Cai Wenming Zheng Tong Zhang Qiang Li Zhen Cui Jiayin Ye

作者单位: Key Laboratory of Child Development and Learning Science,Ministry of Education,Research Center for Learning Science,Southeast University,Nanjing 210096,China

会议类型: 国际会议

会议名称: 第七届全国模式识别学术会议(The 7th Chinese Conference on Pattern Recognition,CCPR2016)

会议地点: 成都

会议语种:英文

页码: 679-691

在线出版日期: 2016-11-03（万方平台首次上网日期，不代表论文的发表时间）