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
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;
Conference_Titel :
Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-2465-6
DOI :
10.1109/MSNA.2012.6324600
