Rapid Summarisation and Browsing of Video Sequences

Abstract

This paper presents a strategy for rapid summarisation and browsing of video sequences. The input video is first transformed into a sequence of representative feature vectors. Using this representation a utility function is designed that assigns high reward to subsequences of keyframes that are maximally distinct and individually carry the most information. For a specified level of detail and endpoints the keyframe sequence that maximises this utility function can be obtained by a non-iterative Dynamic Programming procedure, thus allowing the user to efficiently zoom in on any part or all of the video sequence. For the sake of compactness and clarity the working of the algorithm is illustrated on a television commercial.