Accurate and robust method for detecting video shot boundaries

Many shot boundary detection methods have been proposed in recent years. Comparison studies have revealed that, among the existing methods, the local histogram-based method gives the highest precision rate if the highest shot boundary detection rate is not the first priority. In this paper, we present a new shot boundary detection method that surpasses the local histogram-based method in both the boundary detection rate and the precision rate. We propose a novel method of extracting color distributions from video frames to effectively suppress both the intraframe and the inter-frame color variations caused by noise, minor illumination changes, as well as camera and object motions. We also provide a systematic approach to combine the color and the spatial features of video frames for more accurate shot boundary detection. The experimental evaluation confirms the superior performance of our proposed method.