Abstract
Nowadays, along with the aging of population and declining birthrate factors, how to provide the elderly care system is a major issue. We want to use the technology of face detection and facial expression recognition which have been developed in recent years to identify facial expressions with pain. If we could detect the pain expression, it may help people who are in accident, such as heart attack.This thesis uses Active Appearance Model method to detect location of face features. Then by using the feature points of Active Appearance Model, we extract feature points as shape feature then eliminate effect of head rotation in shape feature. We use the feature points of Active Appearance Model to select region of face, then use variance of regions to determine texture feature. Final, we use the Multiple Kernels Learning method as a classifier, which improves the problem about choosing a best kernel in Support Vector Machine. By using Multiple Kernels Learning method, we can easily control the features and know the importance of each kind of features.Finally, in our experimental results, we show not only recognizing facial expressions with pain in a single image, but also recognizing facial expressions with pain in a video. We can identify the facial expression that a patient feels pain and scream, and the facial expression that a patient feels pain and bear it. That is totally different, but both types of pain are recognized.