NDLI: Fusion of transformed shallow features for facial expression recognition

Content Provider	IET Digital Library
Author	Bougourzi, Fares Mokrani, Karim Ruichek, Yassine Dornaika, Fadi Ouafi, Abdelkrim Ahmed, Abdelmalik Taleb
Abstract	Facial expression conveys important signs about the human affective state, cognitive activity, intention and personality. In fact, the automatic facial expression recognition systems are getting more interest year after year due to its wide range of applications in several interesting fields such as human computer/robot interaction, medical applications, animation and video gaming. In this study, the authors propose to combine between different descriptors features (histogram of oriented gradients, local phase quantisation and binarised statistical image features) after applying principal component analysis on each of them to recognise the six basic expressions and the neutral face from the static images. Their proposed fusion method has been tested on four popular databases which are: JAFFE, MMI, CASIA and CK+, using two different cross-validation schemes: subject independent and leave-one–subject-out. The obtained results show that their method outperforms both the raw features concatenation and state-of-the-art methods.
Starting Page	1479
Ending Page	1489
Page Count	11
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 9, Jul (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.6235
Journal	IET Image Processing
Publisher Date	2019-04-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Animation Automatic Facial Expression Recognition System Basic Expressions Cognitive Activity Computer Vision And Image Processing Technique Different Cross-validation Scheme Different Descriptors Features Emotion Recognition Face Recognition Feature Extraction Fusion Method Human Affective State Human Computer/robot Interaction Image Recognition Image Representation Important Signs Intention Interest Year Interesting Field Local Phase Quantisation Medical Application Optical, Image And Video Signal Processing Oriented Gradients Personality Principal Component Analysis Raw Feature Concatenation State-of-the-art Method Static Image Statistical Analysis Statistical Image Feature Statistics Transformed Shallow Feature Video Gaming
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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