Shot boundary detection and key frame extraction for sports video summarization based on spectral entropy and mutual information

Abstract

Video Summarization methods attempt to abstract the main occurrences, scenes, or objects in a clip in order to provide an easily interpreted synopsis of the video. This is an essential task in video analysis and indexing applications. New methods for detecting shot boundaries in video sequences and extracting key frames using metrics based on information theory are proposed in this work. The method for shot cut detection relies on the mutual information between the frames. The method for key frame extraction uses the difference of entropy value computed from eigen value matrix of consecutive frames to decide which frames to choose as key frame. The proposed method captures satisfactorily the visual content of the shot. The information theory measure provides the better results because it exploits the inter-frame information in a more compact way. It can also be successfully compared to other methods published in literature. The method for key frame extraction employs entropy measure computed on eigen values of frames to reduce complexity of computation. The proposed algorithm can capture the important yet salient content as the key frame. Its robustness and adaptability are validated by experiments with various kinds of video sequences. © 2013 Springer.