Recent years have seen a rapid increase in the size of digital media collections. Because emotion is an important component in the human classification and retrieval of digital media, emotional semantic detection from multimedia has been an active research area in recent decades. This chapter introduces and surveys advances in this area. First, the authors propose a general frame of research on affective multimedia content analysis, which includes physical, psychological and physiological space, alongside the relationships between the three. Second, the authors summarize research conducted on emotional semantic detection from images, videos, and music. Third, three typical archetypal systems are introduced. Last, explanations of several critical problems that are faced in database, the three spaces, and the relationships are provided, and some strategies for problem resolution are proposed.
Towards Neural-Symbolic AI for Media Understanding