a user attention model for video summarization
Automatic generation of video summarization is one of the key techniques in video management and browsing. In this paper, we present a generic framework of video summarization based on the modeling of viewer's attention. Without fully semantic understanding of video content, this framework takes advantage of understanding of video content, this framework takes advantage of computational attention models and eliminates the needs of complex heuristic rules in video summarization. A set of methods of audio-visual attention model features are proposed and presented. The experimental evaluations indicate that the computational attention based approach is an effective alternative to video semantic analysis for video summarization.
user attention model attention model video video summarization generation generation management browse paper semantic understandability contention computation complexity heuristics rules method feature experimentation evaluation effect semantic analysis  framework  skimming audio video content analysis visual attention generic