Authors:
Tanwi Mallick
;
Palash Goyal
;
Partha Pratim Das
and
Arun Kumar Majumdar
Affiliation:
Indian Institute of Technology, India
Keyword(s):
Facial Expression Recognition, Emotion Recognition, Kinect Face Tracking Library (KFTL), Facial Action Coding System (FACS), Action Units (AU), Artificial Neural Network (ANN).
Abstract:
Facial expression classification and emotion recognition from gray-scale or colour images or videos have been extensively explored over the last two decades. In this paper we address the emotion recognition problem using Kinect 1.0 data and the Kinect Face Tracking Library (KFTL). A generative approach based on facial muscle movements is used to classify emotions. We detect various Action Units (AUs) of the face from the feature points extracted by KFTL and then recognize emotions by Artificial Neural Networks (ANNs) based on the detected AUs. We use six emotions, namely, Happiness, Sadness, Fear, Anger, Surprise and Neutral for our work and appraise the strengths and weaknesses of KFTL in terms of feature extraction, AU computations, and emotion detection. We compare our work with earlier studies on emotion recognition from Kinect 1.0 data.