A Novel Approach to Video Transition Detection Based on Machine Learning
Lin Lin · Journal of Guangxi Normal University · 2008
Video transition detection plays an important role in many tasks of video analysis.Aiming at the target application of commercial detection in news video,this paper tackles the problem in a unified framework and proposes an alternative classification strategy.This method is made up of two phases.In the first stage,SVM is employed to classify the transitions into three classes: non-transition,cut,and big-transition.In the second stage,the focus is on the discrimination of the rapid motion situation and gradual transition based on another set of features.Apart from the new classification strategy proposed in this paper,imbalanced data classification issue is also taken into consideration,which has not received sufficient attention in previous work.Experimental results show that the new method is effective.