JIPS (한국정보처리학회)
Current Result Document : 90 / 91
| 한글제목(Korean Title) |
Video Expression Recognition Method Based on Spatiotemporal Recurrent Neural Network and Feature Fusion |
| 영문제목(English Title) |
Video Expression Recognition Method Based on Spatiotemporal Recurrent Neural Network and Feature Fusion |
| 저자(Author) |
Xuan Zhou
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| 원문수록처(Citation) |
VOL 17 NO. 02 PP. 0337 ~ 0351 (2021. 04) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Automatically recognizing facial expressions in video sequences is a challenging task because there is little direct correlation between facial features and subjective emotions in video. To overcome the problem, a video facial expression recognition method using spatiotemporal recurrent neural network and feature fusion is proposed. Firstly, the video is preprocessed. Then, the double-layer cascade structure is used to detect a face in a video image. In addition, two deep convolutional neural networks are used to extract the time-domain and airspace facial features in the video. The spatial convolutional neural network is used to extract the spatial information features from each frame of the static expression images in the video. The temporal convolutional neural network is used to extract the dynamic information features from the optical flow information from multiple frames of expression images in the video. A multiplication fusion is performed with the spatiotemporal features learned by the two deep convolutional neural networks. Finally, the fused features are input to the support vector machine to realize the facial expression classification task. The experimental results on cNTERFACE, RML, and AFEW6.0 datasets show that the recognition rates obtained by the proposed method are as high as 88.67%, 70.32%, and 63.84%, respectively. Comparative experiments show that the proposed method obtains higher recognition accuracy than other recently reported methods.
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| 키워드(Keyword) |
Double Layer Cascade Structure
Facial Expression Recognition
Feature Fusion
Image Detection
Spatiotemporal Recursive Neural Network
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| 파일첨부 |
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