NDLI: Deep facial emotion recognition in video using eigenframes

Content Provider	IET Digital Library
Author	Hajarolasvadi, Noushin Demirel, Hasan
Abstract	Recently, video-based facial emotion recognition (FER) has been an attractive topic in the computer vision society. However, processing several hundreds of frames for a single video of a particular emotion is not efficient. In this study, the authors propose a novel approach to obtain a representative set of frames for a video in the eigenspace domain. Principal component analysis (PCA) is applied to a single emotional video extracting the most significant eigenframes representing the temporal motion variance embedded in the video. Given that faces are segmented and normalised, the variance captured by PCA is attributed to the facial expression dynamics. The variation in the temporal domain is mapped to the eigenspace reducing the redundancy. The proposed approach is used to extract the input eigenframes. Later, VGG-16, ResNet50, and 2D and 3D CNN architectures called eigenFaceNet are trained on the RML, eNTERFACE'05, and AFEW 6.0 databases. The experimental results are superior to the state-of-the-art by 8 and 4% for RML, eNTERFACE'05 databases, respectively. The performance achievement is also coupled with a reduction in the computational time.
Starting Page	3536
Ending Page	3546
Page Count	11
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 14, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/14
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.1566
Journal	IET Image Processing
Publisher Date	2020-09-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision Computer Vision And Image Processing Technique Computer Vision Society Eigenspace Domain Emotion Recognition Face Recognition Facial Expression Dynamics Image Motion Analysis Image Recognition Image Representation Input Eigenframes PCA Principal Component Analysis Single Emotional Video Single Video Statistics Temporal Domain Temporal Motion Variance Video Signal Processing Video-based Facial Emotion Recognition
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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