Analysis of Customer Emotion from Video based Feedback of a Product
E Bharathi, M Bagyalakshmi, G Ambika, G Priyanka · International Journal of Scientific Research in Computer Science Engineering and Information Technology · 2019
Due to the high levels of competition in a global market, companies have put more effort on building strong customer relationships and increasing customer satisfaction levels. Now-a-days due to technological improvements in information and communication technologies gives a highly anticipated key contributor to improve the customer experience and satisfaction in service episodes is through the application of video analytics, such as to evaluate the customer’s emotions over the complete service cycle. Currently, emotion recognition from video could be a difficult analysis space. One of the foremost effective solutions to deal with this challenge is to utilize each audio and visual part as two sources contained within the video knowledge to form an overall assessment of the emotion. The combined use of audio and visual knowledge sources presents further challenges, such as determining the optimal data fusion technique prior to classification. In this paper, we propose an audio–visual emotion recognition system to detect the universal six emotions (happy, angry, sad, disgust, surprise, and fear) from video data. The detected customer emotions are then mapped and translated to provide client satisfaction scores. The projected client satisfaction video analytics system will operate over video conferencing or video chat. The effectiveness of our proposal is verified through numerical results.