中国科学院重庆绿色智能技术研究院机构知识库

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	From macro to micro expression recognition: Deep learning on small datasets using transfer learning
	Peng, Min1; Wu, Zhan2; Zhang, Zhihao2; Chen, Tong2
	2018
摘要	This paper presents the methods used in our submission to 2018 Facial Micro-Expression Grand Challenge (MEGC). The object of the challenge is to recognize micro-expression in two provided databases, including holdout-database recognition and composite database recognition. Considering the small size of the databases, we follow a rout of transfer learning to implement convolutional neural network to recognize the micro-expression. ResNet10 pre-trained on ImageNet dataset was fine-tuned on macro-expression datasets with large size and then on the provided micro-expression datasets. Experimental results show that the method can achieve weighted average recall (WAR) of 0.561 and unweighted average recall (UAR) of 0.389 in Holdout-database Evaluation Task, and F1 Score of 0.64 in Composite Database Evaluation Task, which are much higher than what baseline methods (LBP-TOP, HOOF, HOG3D) can achieve. © 2018 IEEE.
语种	英语
DOI	10.1109/FG.2018.00103
会议(录)名称	13th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2018
页码	657-661
收录类别	EI
会议地点	Xi'an, China
会议日期	May 15, 2018 - May 19, 2018