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http://dx.doi.org/10.9717/kmms.2022.25.2.215

A Study on Sentiment Pattern Analysis of Video Viewers and Predicting Interest in Video using Facial Emotion Recognition  

Jo, In Gu (Dept. of Information Convergence Eng., Graduate School, Pusan National University)
Kong, Younwoo (School of Computer Science and Eng., Pusan National University)
Jeon, Soyi (School of Computer Science and Eng., Pusan National University)
Cho, Seoyeong (School of Computer Science and Eng., Pusan National University)
Lee, DoHoon (School of Computer Science and Eng., Pusan National University)
Publication Information
Journal of Korea Multimedia Society / v.25, no.2, 2022 , pp. 215-220 More about this Journal
Abstract
Emotion recognition is one of the most important and challenging areas of computer vision. Nowadays, many studies on emotion recognition were conducted and the performance of models is also improving. but, more research is needed on emotion recognition and sentiment analysis of video viewers. In this paper, we propose an emotion analysis system the includes a sentiment analysis model and an interest prediction model. We analyzed the emotional patterns of people watching popular and unpopular videos and predicted the level of interest using the emotion analysis system. Experimental results showed that certain emotions were strongly related to the popularity of videos and the interest prediction model had high accuracy in predicting the level of interest.
Keywords
Emotion Recognition; Deep Neural Network; Facial Image Classification; Sentiment Analysis;
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