Emotion Recognition based on Multimodel: Physical - Bio Signals and Video Signal

Abstract

Today, detecting and classifying emotions has become an important item of research and life. Emotion detection and classification are becoming more detailed and accurate thanks to development of various fields such as electronics, sensors or computer engineering. Emotion recognition methods are studied using different data collection methods and one of the most popular and effective methods is the use of physicalbio sensors. Physicalbio sensors -based approaches can provide accurate, sustainable biological information with external influences and interferences.Especially when compared with other approaches such as image processing, video processing. In this paper, we describe a method of classifying and assessing emotions based on a combination of signals collected from physicalbio sensors, video collection and machine learning methods. Specifically, we will describe the platform of a physicalbio signal collection system, the process of collecting information and the processing information system used to identify how emotional behavior is characterized. We have also shown that a combination of physicalbio sensors acquisition systems, video collection and machine learning methods can provide identification performance with an accuracy of 83.2%.