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 a 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.