CASIA OpenIR  > 模式识别国家重点实验室  > 语音交互
Multi-scale Temporal Modeling for Dimensional Emotion Recognition in Video
Linlin Chao; Jianhua Tao; Minghao Yang; Ya Li
2014
会议名称Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge
会议录名称Proceedings of the 4th International Workshop on Audio/Visual Emotion Challenge
页码11-18
会议日期2014-11
会议地点Orlando, Florida
摘要Understanding nonverbal behaviors in human machine interaction is a complex and challenge task. One of the key aspects is to recognize human emotion states accurately. This paper presents our effort to the Audio/Visual Emotion Challenge (AVEC'14), whose goal is to predict the continuous values of the emotion dimensions arousal, valence and dominance at each moment in time. The proposed method utilizes deep belief network based models to recognize emotion states from audio and visual modalities. Firstly, we employ temporal pooling functions in the deep neutral network to encode dynamic information in the features, which achieves the first time scale temporal modeling. Secondly, we combine the predicted results from different modalities and emotion temporal context information simultaneously. The proposed multimodal-temporal fusion achieves temporal modeling for the emotion states in the second time scale.  Experiments results show the efficiency of each key point of the proposed method and competitive results are obtained.
关键词Affective Computing
收录类别EI
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/11846
专题模式识别国家重点实验室_语音交互
通讯作者Linlin Chao
作者单位Institute of Automation, Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Linlin Chao,Jianhua Tao,Minghao Yang,et al. Multi-scale Temporal Modeling for Dimensional Emotion Recognition in Video[C],2014:11-18.
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