NDLI: Video-based detection of the clinical depression in adolescents

Content Provider	IEEE Xplore Digital Library
Author	Maddage, N.C. Senaratne, R. Low, L.-S.A. Lech, M. Allen, N.
Copyright Year	2009
Description	Author affiliation: Obtained his PhD in 2008 and is currently working as an independent researcher (Senaratne, R.) \|\| ORYGEN Research Centre and Dept of Psychology, University of Melbourne, Melbourne 3010, Australia (Allen, N.) \|\| Margaret Lech are with the School of Electrical and Computer Engineering, RMIT University, Melbourne 3001, Australia (Maddage, N.C.; Low, L.-S.A.; Lech, M.)
Abstract	We proposed a framework to detect the video contents of depressed and non-depressed subjects. First we characterized the expressed emotions in the video stream using Gabor wavelet features extracted at the facial landmarks which were detected using landmark model matching algorithm. Depressed and non-depressed class models were constructed using Gaussian Mixture models. Using 8 hours of video recordings, an hour of video recording per subject, and both gender and class balanced, we examined the effectiveness of both gender based and gender independent modeling approaches for depressed and non-depressed content classification. We found that the gender based content modeling approach improved the classification accuracy by 6% compared to the gender independent modeling approach, achieving 78.6% average accuracy.
Starting Page	3723
Ending Page	3726
File Size	916259
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5334815
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face detection Detectors Active shape model Feature extraction Video recording USA Councils Video sequences Supervised learning Computer vision Libraries
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
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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