Two-stage hierarchical video summary extraction to match low-level user browsing preferences
A compact summary of video that conveys visual content at various levels of detail enhances user interaction significantly. In this paper, we propose a two-stage framework to generate MPEG-7-compliant hierarchical key frame summaries of video sequences. At the first stage, which is carried out off-line at the time of content production, fuzzy clustering and data pruning methods are applied to given video segments to obtain a nonredundant set of key frames that comprise the finest level of the hierarchical summary. Here, the number of key frames allocated to each shot or segment is determined dynamically and without user supervision through the use of cluster validation techniques. A coarser summary is generated on-demand in the second stage by reducing the number of key frames to match the low-level browsing preferences of a user. The proposed method has been validated by experimental results on a collection of video programs.
fuzzy clustering cluster validation mpeg-7 video databases visual summarization