Affective content based music video paring system using real coded GA
Chung-Hsiang Hsueh, Tian–Li Yu · 2012
As the high quality cameras, video editing software and music composition software are more available, making videos becomes popular. However, processing home videos is time-consuming. Some popular commercial software such as iMovie and Adobe Premiere provide user-friendly interface to help people make films on their own, but adding adequate music to a clip is still a non-trivial work that highly depends on human feelings and emotions. This paper proposes an emotion-based evolutionary music video pairing system by utilizing affective information of videos and musics to remedy this problem. Empirical results show that our system is capable of pairing videos with adequate musics and self-adapting to human preferences.