Automatic Video Shot Boundary Detection of News Stream Using a High-Level Fuzzy Petri Net

With the advent of digital era, the users have difficulty in using and absorbing overwhelming information brought out by technological advances in multimedia. Thus, the development of video summarization enables users to have a general idea about videos in a short time. This study focuses on the shot change, a part of the video summarization, to conduct an experimental sample on news programs. Moreover, a high-level fuzzy Petri net model is presented to describe boundary frames combination which indicates a shot boundary used for video frame sequence to detect both cut transitions and gradual transitions. The experimental results manifest it saves a lot of time and reduces the occurrence of improper shot change caused by the motions of objects and cameras when comparing this method with human labor.