Video shot boundary detection with local feature post refinement

Video shot boundary detection is a fundamental step for content base video analysis and has been widely studied in recent years. In this paper, a novel shot boundary detection algorithm is proposed. The algorithm uses feature space kernel smoothing to segment video into shots. The method is demonstrated to have high accuracy in both cuts and gradual transition detection. For flashlights and fast background change which cause the false detection, a post refinement strategy using local feature analysis is also studied in this paper. The effectiveness of the method is also verified by the experiments.