NDLI: Personalised-face neutralisation using best-matched face shape with a neutral-face database

Content Provider	IET Digital Library
Author	Petpairote, Chayanut Madarasmi, Suthep Chamnongthai, Kosin
Abstract	Conventional personalised-face neutralisation methods use facial-expression databases; however, the database creation and maintenance is a tedious process, and should be minimised. Moreover, face-shape template should be also considerably used due to its crucial factor. This study proposes a personalised-face neutralisation method using best-matched face-shape template with neutral-face database. In personalised-face neutralisation, the best-matched face-shape template which is assumed as the most similar to the neutralisation expression face is found based on coarse-to-fine concept, and used for warping textures. Additionally, closed eyes are detected and opened up by using eye shape of the best-matched face shape, and mixed intensities of original closed-eye and the best-matched one. To evaluate the performance of the proposed method, experiments were performed using the CMU Multi-PIE database and the results reveal that the proposed method reduces gradient mean square error 0.07% on average and improves face recognition accuracy by 1.13% approximately comparing with the conventional method, while requiring only a single neutral database without expression images.
Starting Page	252
Ending Page	260
Page Count	9
ISSN	17519632
Volume Number	12
e-ISSN	17519640
Issue Number	Issue 3, Apr (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/12/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2017.0352
Journal	IET Computer Vision
Publisher Date	2017-10-24
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Best-matched Face-shape Template Closed Eyes Detection CMU MultiPIE Database Coarse-to-fine Concept Computer Vision And Image Processing Technique Database Creation Database Maintenance Emotion Recognition Eye Eye Shape Face Recognition Face Recognition Accuracy Facial-expression Database Gradient Mean Square Error Reduction Gradient Method Image Recognition Image Texture Interpolation And Function Approximation Mean Square Error Method Neutral-face Database Neutralisation Expression Face Numerical Analysis Object Detection Personalised-face Neutralisation Method Spatial And Pictorial Database Texture Warping Visual Database
Content Type	Text
Resource Type	Article
Subject	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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