Many algorithms have been proposed for detecting video shot boundaries and classifying shot and shot transition types. Few published studies compare available algorithms, and those that do have looked at limited range of test material. This paper presents a comparison of several shot boundary detection and classification techniques and their variations including histograms, discrete cosine transform, motion vector, and block matching methods. The performance and ease of selecting good thresholds for these algorithms are evaluated based on a wide variety of video sequences with a good mix of transition types. Threshold selection requires a trade-off between recall and precision that must be guided by the target application.
In REF , after comparing several different methods of shot boundary detection using a variety of video content types, Borezcky and Rowe concluded that histogram-based methods were more successful than others, but that shot boundary detection thresholds must be guided by the target application.
Comparison of Video Shot Boundary Detection Techniques
J. Electronic Imaging
J. Electronic Imaging
Computer Science