NDLI: Smile detection using hybrid face representation

Content Provider	Springer Nature Link
Author	Arigbabu, Olasimbo Ayodeji Mahmood, Saif Ahmad, Sharifah Mumtazah Syed Arigbabu, Abayomi A.
Copyright Year	2015
Abstract	Smile detection has attracted considerable amount of research interests in the domain of computer vision. It possesses several potential applications in gaming, human-to-computer and human-to-human interaction. This paper investigates the challenging problem of smile detection from face images acquired under unconstrained conditions. First, a locally weighted multiblock shape-texture descriptor is proposed to extract detailed local and global information from faces with diverse variations such as orientation, illumination, pose, and occlusion. The proposed technique combines the robustness of pyramid histogram of oriented gradient and local binary pattern for image feature representation using an adaptive local weight assignment. By locally weighting the descriptors from very dense patches of the image, we induce discriminating local spatial context to the distribution of the descriptions from the face image. Second, in order to minimize redundancy and extract the most relevant facial information from the feature vectors, a correlation based filter feature selection approach is adopted. Finally, kernel based classifiers such as support vector machine and kernel extreme learning machine are utilized for performing classification. Based on our findings, the proposed framework provides very competitive detection rate to related approaches that have exploited image alignment as an important stage for improving performance of smile detection.
Starting Page	415
Ending Page	426
Page Count	12
File Format	PDF
ISSN	18685137
Journal	Journal of Ambient Intelligence and Humanized Computing
Volume Number	7
Issue Number	3
e-ISSN	18685145
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-12-07
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Smile detection Unconstrained face images Local feature descriptors Feature selection Kernel extreme learning machine Support vector machine Computational Intelligence Artificial Intelligence (incl. Robotics) Robotics and Automation User Interfaces and Human Computer Interaction
Content Type	Text
Resource Type	Article
Subject	Computer Science

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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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