Adaptive metric learning with deep neural networks for video-based facial expression recognition
Liu, X. F.; Ge, Y. B.; Yang, C.; Jia, P.
刊名Journal of Electronic Imaging
2018
卷号27期号:1页码:9
关键词metric learning video-based facial expression recognition deep learning Engineering Optics Imaging Science & Photographic Technology
ISSN号1017-9909
DOI10.1117/1.Jei.27.1.013022
英文摘要Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N + M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches. (c) 2018 SPIE and IS&T
内容类型期刊论文
源URL[http://ir.ciomp.ac.cn/handle/181722/60892]  
专题中国科学院长春光学精密机械与物理研究所
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GB/T 7714
Liu, X. F.,Ge, Y. B.,Yang, C.,et al. Adaptive metric learning with deep neural networks for video-based facial expression recognition[J]. Journal of Electronic Imaging,2018,27(1):9.
APA Liu, X. F.,Ge, Y. B.,Yang, C.,&Jia, P..(2018).Adaptive metric learning with deep neural networks for video-based facial expression recognition.Journal of Electronic Imaging,27(1),9.
MLA Liu, X. F.,et al."Adaptive metric learning with deep neural networks for video-based facial expression recognition".Journal of Electronic Imaging 27.1(2018):9.
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