NDLI: Regional adaptive affinitive patterns (RADAP) with logical operators for facial expression recognition

Content Provider	IET Digital Library
Author	Mandal, Murari Verma, Monu Mathur, Sonakshi Vipparthi, Santosh Kumar Murala, Subrahmanyam Kumar, Deveerasetty Kranthi
Abstract	Automated facial expression recognition plays a significant role in the study of human behaviour analysis. In this study, the authors propose a robust feature descriptor named regional adaptive affinitive patterns (RADAP) for facial expression recognition. The RADAP computes positional adaptive thresholds in the local neighbourhood and encodes multi-distance magnitude features which are robust to intra-class variations and irregular illumination variation in an image. Furthermore, they established cross-distance co-occurrence relations in RADAP by using logical operators. They proposed XRADAP, ARADAP, and DRADAP using xor, adder and decoder, respectively. The XRADAP engrains the quality of robustness to intra-class variations in RADAP features using pairwise co-occurrence. Similarly, ARADAP and DRADAP extract more stable and illumination invariant features and capture the minute expression features which are usually missed by regular descriptors. The performance of the proposed methods is evaluated by conducting experiments on nine benchmark datasets Cohn–Kanade+ (CK+), Japanese female facial expression (JAFFE), Multimedia Understanding Group (MUG), MMI, OULU-CASIA, Indian spontaneous expression database, DISFA, AFEW and Combined (CK+, JAFFE, MUG, MMI & GEMEP-FERA) database in both person dependent and person independent setup. The experimental results demonstrate the effectiveness of the proposed method over state-of-the-art approaches.
Starting Page	850
Ending Page	861
Page Count	12
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 5, Apr (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5683
Journal	IET Image Processing
Publisher Date	2019-02-15
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automated Facial Expression Recognition System Computer Vision And Image Processing Technique Cross-distance Co-occurrence Relations Emotion Recognition Face Recognition Facial Expressions Feature Extraction Human Behaviour Analysis Human Emotional State Illumination Invariant Feature Image Classification Image Recognition Image Representation Indian Spontaneous Expression Database Intra-class Variations Irregular Illumination Variation Logical Operators Minute Expression Feature Multidistance Magnitude Feature Positional Adaptive Thresholds RADAP Feature Regional Adaptive Affinitive Pattern Robust Feature Descriptor Stable Invariant Feature Statistics
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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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