Effective Detection of Various Wipe Transitions

Automatic detection of wipes and their frame ranges is important for the purpose of reliable video parsing and video database indexing. Wipes are difficult to detect because of the complexity and variety of the transition effects. Many of the existing wipe detection algorithms could detect only a few wipe effects. The false/miss detection problem caused by motion is also very serious. In this paper, we propose a novel wipe detection algorithm that can detect most wipe effects with accurate frame ranges. We carefully model a wipe based on its nature and then use the model to filter out possible confusion caused by motion or other transition effects. More precisely, properties of independence and completeness are proposed to characterize an ideal wipe; frame ranges of potential wipes are located by finding sequences which are a close approximation to an ideal wipe. Bayes rule is applied to each potential wipe to statistically estimate an adaptive threshold for the purpose of wipe verification. Experiment results on videos with different genres show that the proposed methodology can be used to detect various wipe effects effectively