NDLI: Emotion recognition from facial expressions using hybrid feature descriptors

Content Provider	IET Digital Library
Author	Kalsum, Tehmina Anwar, Syed Muhammad Majid, Muhammad Khan, Bilal Ali, Sahibzada Muhammad
Abstract	Here, a hybrid feature descriptor-based method is proposed to recognise human emotions from their facial expressions. A combination of spatial bag of features (SBoFs) with spatial scale-invariant feature transform (SBoF-SSIFT), and SBoFs with spatial speeded up robust transform are utilised to improve the ability to recognise facial expressions. For classification of emotions, K-nearest neighbour and support vector machines (SVMs) with linear, polynomial, and radial basis function kernels are applied. SBoFs descriptor generates a fixed length feature vector for all sample images irrespective of their size. Spatial SIFT and SURF features are independent of scaling, rotation, translation, projective transforms, and partly to illumination changes. A modified form of bag of features (BoFs) is employed by involving feature's spatial information for facial emotion recognition. The proposed method differs from conventional methods that are used for simple object categorisation without using spatial information. Experiments have been performed on extended Cohn–Kanade (CK+) and Japanese female facial expression (JAFFE) data sets. SBoF-SSIFT with SVM resulted in a recognition accuracy of 98.5% on CK+ and 98.3% on JAFFE data set. Images are resized through selective pre-processing, thereby retaining only the information of interest and reducing computation time.
Starting Page	1004
Ending Page	1012
Page Count	9
ISSN	17519659
Volume Number	12
e-ISSN	17519667
Issue Number	Issue 6, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/12/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0499
Journal	IET Image Processing
Publisher Date	2018-01-22
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra CK+ Computer Vision And Image Processing Technique Data Analysis Data Handling Technique Emotion Recognition Emotions Classification Extended Cohn-Kanade Data Sets Face Recognition Facial Emotion Recognition Facial Expressions Fixed Length Feature Vector Human Emotions Recognition Hybrid Feature Descriptor-based Method Hybrid Feature Descriptors Image Classification Image Recognition JAFFE Japanese Female Facial Expression Data Sets K-nearest Neighbour Knowledge Engineering Technique Linear Kernels Neural Computing Technique Object Categorisation Polynomial Kernels Projective Transforms Radial Basis Function Kernels Radial Basis Function Network SBoF-SSIFT Selective Preprocessing Spatial Bag of Feature Spatial Scale-invariant Feature Transform Support Vector Machine SURF Feature SVM Vector
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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