Audio-Video Based Multimodal Emotion Recognition Using SVMs and Deep Learning

摘要：

　　In this paper,we explored a multi-feature based classification framework for the Multimodal Emotion Recognition Challenge,which is part of the Chinese Conference on Pattern Recognition(CCPR 2016).The task of the challenge is to recognize one of eight facial emotions in short video segments extracted from Chinese films,TV plays and talk shows.In our framework,both traditional methods and Deep Convolutional Neural Network(DCNN)methods are used to extract various features.With different features,different classifiers are trained to predict video emotion labels.Moreover,a decision-level fusion method is explored to aggregate these different prediction results.According to the results on the competition database,our method shows better effectiveness on Chinese facial emotion.

关键词： Emotion recognition Spatio-temporal information Deep learning Decision-level fusion Deep convolutional neural network

作者: Bo Sun Qihua Xu Lejun Yu Liandong Li Qinglan Wei

作者单位: College of Information Science and Technology,Beijing Normal University,Beijing,Peoples Republic of College of Information Science and Technology,Beijing Normal University,Beijing,Peoples Republic of

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: 621-631

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）