Facial Expression Recognition Using Weighted Distance Transform

Abstract

Facial emotions of human transfer non-verbal signal, which have a dynamic role in interactive communication. Human machine interface evolves according to facial expression recognition because both have a significant relationship. Psychology, ethical science and robotics are necessary applications of facial expression recognition. There have been a lot of work already done on feature extraction, face detection and the famous techniques used for expression recognition. Weighted distance is the basic method of this research. It is used for recognition of all basic human emotions, angry, happy, disgust, fear, neutral, sad and surprise. For the extraction of weighted distance paths, the fast marching algorithm is used and seed point has been taken on the nose tip of the human face. Diverse number of paths also has been taken, and it has an effect on facial expression recognition. Intensity variation is the main motivation to use Weighted Distance Transform. Twenty points are labelled for the calculation of feature vectors. Different mathematical measures are calculated as a feature vector of this geometric representation. In classification KNN is used and it illustrates reasonable result. In the end validation is done with famous techniques of facial expression recognition.