NDLI: Eye gaze direction detection using Principal Component Analysis and appearance based methods

Content Provider	IEEE Xplore Digital Library
Author	Yilmaz, C.M. Kose, C.
Copyright Year	2015
Description	Author affiliation: Bilgisayar Muhendisligi Bolumu, Karadeniz Teknik Univ., Trabzon, Turkey (Yilmaz, C.M.; Kose, C.)
Abstract	User's gaze on computer screen is widely being used in human computer interaction, virtual reality, computer game industry, usability tests, improving the quality of physically disabled people and drowsiness detection. In this work, gaze image data and computer screen are spatially mapped using appearance based video oculography methods. Furthermore, gazing directions of left, right, lower, upper, center and closed eye state are detected. In order to do this, a new gaze database is created and color space channels which best describes gaze images' appearance are selected. Users' gaze direction is detected using Principal Component Analysis (PCA) feature extraction method and various machine learning approaches. Evaluation of best approaches is performed by using the resulting classification accuracy of applied methods. Eventually, PCA and Artificial Neural Network (ANN) approach shows 95.36% estimation accuracy of gazes in five different direction and closed eye state, %98.0 average accuracy of left/right and up/down directions, which is comparable to the results in literature.
Starting Page	1050
Ending Page	1053
File Size	395378
Page Count	4
File Format	PDF
ISBN	9781467373869
DOI	10.1109/SIU.2015.7130013
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-16
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computers Human computer interaction eye gaze gaze direction detection Accuracy appearance based video-oculography Estimation Artificial neural networks Feature extraction human computer interaction principal component analysis Principal component analysis
Content Type	Text
Resource Type	Article

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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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