We studied the tracking theory based on Candide3 facial model and according to the research we further developed the tracking process. Based on the research of facial tracking, we put forward a dynamic feature extraction method based on six parameters of facial model. We introduced the active appearance model algorithm to locate and track feature points of facial expression, then studied the tr...

Individuals with pervasive developmental disorder (PDD) have difficulty with social communication via emotional facial expressions, but behavioral studies involving static images have reported inconsistent findings about emotion recognition. We investigated whether dynamic presentation of facial expression would enhance subjective perception of expressed emotion in 13 individuals with PDD and 1...

Facial expressions of pain and emotions provide powerful social signals, which impart information about a person's state. Unfortunately, research on pain and emotion expression has been conducted largely in parallel with few bridges allowing for direct comparison of the expressive displays and their impact on observers. Moreover, although facial expressions are highly dynamic, previous research...

It is challenging to track multiple facial features simultaneously in video while rich facial expressions are presented in a human face. To accurately predict the positions of multiple facial features’ contours is important and difficult. This paper proposes a multi-cue prediction model based tracking algorithm. In the prediction model, CAMSHIFT is used to track the face in video in advance, an...

Probing emotional facial expression recognition with the adaptation paradigm is one way to investigate the processes underlying emotional face recognition. Previous research suggests that these processes are tuned to dynamic facial information (facial movement). Here we examined the tuning of processes involved in the recognition of emotional facial expressions to different sources of facial mo...

This article presents a feature-based framework to automatically track 18 facial landmarks for emotion recognition and emotional dynamic analysis. With a new way of using multi-kernel learning, we combine two methods: the first matches facial feature points between consecutive images and the second uses an offline learning of the facial landmark appearance. Matching points results in a jitter-f...