Action movies segmentation and summarization based on tempo analysis

With the advances of digital video analysis and storage technologies, also the progress of entertainment industry, movie viewers hope to gain more control over what they see. Therefore, tools that enable movie content analysis are important for accessing, retrieving, and browsing information close to a human perceptive and semantic level. We proposed an action movie segmentation and summarization framework based on movie tempo, which represents as the delivery speed of important segments of a movie. In the tempo-based system, we combine techniques of the film domain related knowledge (film grammar), shot change detection, motion activity analysis, and semantic context detection based on audio features to grasp the concept of tempo for story unit extraction, and then build a system for action movies segmentation and summarization. We conduct some experiments on several different action movie sequences, and demonstrate an analysis and comparison according to the satisfactory experimental results.