ITERATIVE INCREMENTAL SHOT CLUSTERING ALGORITHM BY HAAR WAVELETS

摘要

Video shot clustering is the basis of other high-level research of multimedia databases applications. This article proposes a novel and efficient shot clustering algorithm for videos by applying the multi-resolution analysis of Haar wavelets which is called MLHC(Multi-Level Hierarchical Clustering). Corresponding to the reconstruction procedures of Haar wavelets, MLHC is designed as a multi-level algorithm. When the algorithm runs to further levels, the clustering results are increasingly credible and precise. After the clustering results achieve a stable status, MLHC stops automatically. Thus it's an iterative incremental clustering algorithm. Each level of MLHC is an independent hierarchical clustering algorithm which resolves the dilemma of choosing proper initial cluster centers for most existing shot clustering algorithms. For each hierarchical level of MLHC, a novel stop criterion is designed to stop the iterative merging procedures and terminates MLHC on this level. By this stop criterion, the clustering results can be obtained automatically without any parameters and the number of clusters can also be estimated at the same time. The theoretical analysis and the extensive experiments witness the efficiency and effectiveness of our proposals.