DocumentCode
1632678
Title
Automatically infant pain recognition based on LDA classifier
Author
Naufal Mansor, M. ; Nazri Rejab, M. ; Hi-Fi Syam, S. ; Hi-Fi Syam B, Addzrull
Author_Institution
Sch. of Mechatron. Eng., Univ. Malaysia Perlis, Kangar, Malaysia
Volume
2
fYear
2012
Firstpage
380
Lastpage
382
Abstract
This paper discusses the challenges and possibilities of infant pain automatic detection and analysis of infant faces in the scene. The first module implements Haar Cascade Classifier to detect the face. Secondly, extracts the features of faces based on Principal Component Analysis. Finally a LDA classifier used to classify the pain score. From the trial, it is found that the identification rate of reaches 93.12%.
Keywords
face recognition; image classification; object detection; principal component analysis; Haar cascade classifier; LDA classifier; automatically infant pain recognition; face detection; infant faces; linear discriminant analysis; principal component analysis; Educational institutions; Feature extraction; Monitoring; Pain; Pediatrics; Principal component analysis; Detection of facial changes; LDA classifier; NICU patient;
fLanguage
English
Publisher
ieee
Conference_Titel
Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
Conference_Location
Sanya
Print_ISBN
978-1-4673-2465-6
Type
conf
DOI
10.1109/MSNA.2012.6324600
Filename
6324600
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