A video summairization tool using two-level redundancy detection for personal video recorders

Storage of video information is experiencing rapid growth as digital broadcasting services have developed. This has rapidly increased video data storage requirements in DVD and hard disc recorders in recent years. We design a video summarization tool for personal video recorders. This tool provides a video summarization function to grasp the original long video content quickly. This tool is with a two-level redundancy detection procedure. After the video parsing step, it removes redundant video content with the hierarchical agglomerative cluster method in the shot level. Impact factors of scenes and key frames are defined, and parts of shots are selected to generate the initial video summary. Finally a repetitive frame segment detection step is used to remove redundant information. We have developed a prototype model and tested this tool on TV series, movies and cartoons data. The experiment results are given to illustrate the proposed tool.