Real World Real-time Automatic Recognition of Facial Expressions

Most facial expression analysis systems attempt to recognize facial expressions from data collected in a highly controlled laboratory with very high resolution frontal faces (face regions greater than 200 x 200 pixels) and cannot handle large head motions. In real environments such as smart meetings, a facial expression analysis system must be able to automatically recognize expressions at lower resolution and handle the full range of head motion. This paper describes a real-time system to automatically recognize facial expressions in relatively low resolution face images (around 50x70 to 75x100 pixels). To handle the full range of head motion, we detect the head instead of the face. Then the head pose is estimated based on the detected head. For frontal and near frontal views of the face, the location and shape features are computed for expression recognition. Our system successfully deals with complex real world interactions, as demonstrated on the PETS2003 dataset.