Automatically infant pain recognition based on LDA classifier

摘要

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%.