Parameter Analysis of the Jensen-Shannon Divergence for Shot Boundary Detection in Streaming Media Applications

Shot boundary detection is an integral part of multimedia, be it video management or video processing. Multiple boundary detection techniques have been developed throughout the years, but are only applicable to very specific instances. The Jensen-Shannon divergence (JSD) is one such a technique that can be implemented to detect the shot boundaries in digital videos. This paper investigates the use of the JSD algorithm to detect shot boundaries in streaming media applications. Furthermore, the effects of the various parameters used by the JSD technique, on the accuracy of the detected boundaries, are quantified by the recall and precision metrics all the while keeping track of how they affect the execution time.