Personalized video adaptation based on video content analysis
Min Gang Xu, Jesse Sheng Jin, Suhuai Luo · 2008
Personalized video adaptation is expected to satisfy individual users' needs on video content. Multimedia data mining plays a significant role of video annotation to meet users' preference on video content. In this paper, a comprehensive solution for personalized video adaptation is proposed based on video content mining. Video content mining targets both cognitive content and affective content. Cognitive content refers to those semantic events, which are very specific for the video domains. Sometimes, users might prefer "emotional decision" to select their interested video content. Therefore, we introduce affective content which causes audiences' strong reactions.