Shot Boundary Detection Using Genetic Algorithm Optimization

This paper presents a novel method for shot boundary detection via an optimization of traditional scoring based metrics using a genetic algorithm search heuristic. The advantage of this approach is that it allows for the detection of shots without requiring the direct use of thresholds. The methodology is described using the edge-change ratio metric and applied to several test video segments from the TREC 2002 video track and contemporary television shows. The shot boundary detection results are evaluated using recall, precision and F1 metrics, which demonstrate that the proposed approach provides superior overall performance when compared to the effective edge-change ratio method. In addition, the convergence of the genetic algorithm is examined to show that the proposed method is both efficient and stable.