Building a Chinese Facial Expression Database for Automatically Detecting Academic Emotions to Support Instruction in Blended and Digital Learning Environments

Abstract

This paper specifically focuses on how to build a Chinese facial expression database collecting the facial expressions of college students and describes a strategy to develop an automatically detecting technique for academic emotions to support teachers making better decisions in blended and digital learning environments. There are some famous worldwide databases of facial emotion expressions, e.g., Amsterdam Dynamic Facial Expression Set (ADFES), Montreal set of facial displays of emotion, or Brazillian FEI database. Their major collections are full facial expression of western people with very limited Asian or Chinese faces. Because some emotion facial expressions might be culturally bounded, it arises the necessity to develop a Chinese facial expression database as a critical step to develop an automatically facial emotion expression dictating technique with high accuracy.