Shot-based similarity measure for content-based video summarization

The rapid development of multimedia applications over the past decade requires efficient methods for video browsing. In this paper, we present an algorithm for video summarization with shot comparison. We analyze video content in the shot level, and we calculate the shot distance using the advanced Hausdorff distance. The advanced Hausdorff distance combines the Hausdorff distance and Boolean model, and it could compare two shots from the global view. When the shot similarity matrix is obtained, we group these video shots into several clusters using the affinity propagation cluster method to remove redundant video content. Performance evaluation on ten video sequences are given to illustrate the proposed algorithm.