An Unified Transition Detection Based on Bipartite Graph Matching Approach

This paper addresses transition detection which consists in identifying the boundary between consecutive shots. In this work, we propose an approach to cope with transition detection in which we define and use a new dissimilarity measure based on the size of the maximum cardinality matching calculated using a bipartite graph with respect to a sliding window. The experiments have used two video datasets which presents a variety of different video genres with 3079 transitions. Our method achieves performance measures similar to the best results found in the literature with a much simpler classification approach.