Video summarization with SOMs
Video summarization is a process where a long video file is converted to a considerably shorter form. The video summary can then be used to facilitate efficient searching and browsing of video files in large video collections. The aim of successful automatic summarization is to preserve as much as possible from the essential content of each video. What is essential is subjective and dependent on the use of the videos and the overall content of the collection. In this paper we present an overview of the SOM-based methodology we have used for video summarization. The method uses temporal trajectories of the best-matching units of frame-wise feature vectors for shot boundary detection and shot similarity assessment. The video material we have used in our experiments comes from NIST's annual TRECVID evaluation for content-based video retrieval systems.