Optical Flow-Based Algorithm Analysis to Detect Human Emotion from Eye Movement-Image Data

Abstract

One of the popular methods for the recognition of human emotions such as happiness, sadness and shock is based on the movement of facial features. Motion vectors that show these movements can be calculated by using optical flow algorithms. In this method, for detecting emotions, the resulted set of motion vectors is compared with a standard facial movement template caused by human emotional changes. In this paper, a new method is introduced to compute the quantity of likeness towards a particular emotion to make decisions based on the importance of obtained vectors from an optical flow approach. The current study uses a feature point tracking technique separately applied to the five facial image regions (eyebrows, eyes, and mouth) to identify basic emotions. Primarily, this research will be focusing on eye movement regions. For finding the vectors, one of the efficient optical flow methods is using the pre-experiment as explained further below.