VIDEO BASED EMOTION DETECTION USING DEEP LEARNING

Abstract: Social networking platforms have become an essential means for communicating feelings to the entire world due to rapid expansion in the Internet era. Several people use textual content, pictures, audio, and video to express their feelings or viewpoints. Text communication via Web-based networking media, on the other hand, is somewhat overwhelming. Every second, a massive amount of unstructured data is generated on the Internet due to social media platforms. Video emotion analysis is one of the hottest topics in the video understanding community to cognize the emotion in videos for affective computing, video recommendation, and so on. Currently, many studies tend to employ different deep structures to model video contents for this task. In fact, audiences responses (e.g., physiological signals and comments) are also important since they are directly related to video emotional content and can reflect the emotions in videos.