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Appl. Sci. 2017, 7(11), 1184; doi:10.3390/app7111184

NIRExpNet: Three-Stream 3D Convolutional Neural Network for Near Infrared Facial Expression Recognition

1,2
,
1,2,* , 1,2
,
1,2
and
1,2
1
Chongqing Key Laboratory of Nonlinear Circuit and Intelligent Information Processing, Southwest University, Chongqing 400715, China
2
School of Electronic and Information Engineering, Southwest University, Chongqing 400715, China
*
Author to whom correspondence should be addressed.
Received: 28 September 2017 / Revised: 26 October 2017 / Accepted: 6 November 2017 / Published: 17 November 2017
(This article belongs to the Section Computer Science and Electrical Engineering)
View Full-Text   |   Download PDF [1610 KB, uploaded 17 November 2017]   |  

Abstract

Facial expression recognition (FER) under active near-infrared (NIR) illumination has the advantages of illumination invariance. In this paper, we propose a three-stream 3D convolutional neural network, named as NIRExpNet for NIR FER. The 3D structure of NIRExpNet makes it possible to extract automatically, not just spatial features, but also, temporal features. The design of multiple streams of the NIRExpNet enables it to fuse local and global facial expression features. To avoid over-fitting, the NIRExpNet has a moderate size to suit the Oulu-CASIA NIR facial expression database that is a medium-size database. Experimental results show that the proposed NIRExpNet outperforms some previous state-of-art methods, such as Histogram of Oriented Gradient to 3D (HOG 3D), Local binary patterns from three orthogonal planes (LBP-TOP), deep temporal appearance-geometry network (DTAGN), and adapt 3D Convolutional Neural Networks (3D CNN DAP). View Full-Text
Keywords: near-infrared facial expression recognition; 3D convolutional neural network; global and local features of facial expression; spatio-temporal features near-infrared facial expression recognition; 3D convolutional neural network; global and local features of facial expression; spatio-temporal features
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Wu, Z.; Chen, T.; Chen, Y.; Zhang, Z.; Liu, G. NIRExpNet: Three-Stream 3D Convolutional Neural Network for Near Infrared Facial Expression Recognition. Appl. Sci. 2017, 7, 1184.

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