Eye movement based emotion recognition using electrooculography

摘要

Emotions play a vibrant role in life as the human reaction or response to a system is purely based on the nature of his emotion, may it be the response to a computer system or to fellow mates. The need and significance of automatic emotion recognition have grown with the emergent role of human computer interface applications and the development of AI based companions or self-assistance system. The development of AI and machine learning systems has paved a brighter way for the optimistic yet accurate emotion recognizing systems. Emotion recognition can be done from any form of response from a person such as text, speech, facial expression or gesture. The proposed system introduces an emotion recognition system, based on human eye movement using electrooculography (EOG) signals. Based on EOG signals emotions are classified as - happy, sad, angry, fear and pleasant. Multi-class Support Vector Machines is used for classifying the processed Electrooculography signals and for feature extraction ICA (Independent Component Analysis) is used. Using these techniques, human emotions are recognized and inputted in an augmented reality (AR) system where the humans can interact or respond to the system.