Discontinuity-Driven Shot Detection Algorithm for Dissolving Shots

Detecting shot boundary plays an essential role in video analysis.Conventional methods work well when the shot is cut or faded in/out,while are inefficient for dissolving shots.This paper proposes a novel detection algorithm that leverages the image discontinuity features to characterize the dissolving behaviors of shots.The algorithm consists of three stages.First,the image discontinuity features are employed to measure the proximities between of neighboring image blocks in each image frame.Then,the features are classified by means of the SVM classifier.Finally,misclassified results are corrected,and dissolving shots are extended.The experiments on TRECVid dataset verified that the proposed algorithm can achieve much higher accuracy and robustness compared with traditional methods.