Shot boundary detection based on SVM and TMRA

Authors:
Wei Fang;Sen Liu;Huamin Feng;Yong Fang
Affiliations:
Telecommunication Engineering College, BUPT University, Beijing, China;Communication Engineering College, YanShan University, Qinhuangdao, China;Key Laboratory of Security and Secrecy of Information, BESTI, Beijing, China;Key Laboratory of Security and Secrecy of Information, BESTI, Beijing, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

Video shot boundary detection (SBD) is an important step in many video applications. In this paper, previous temporal multi-resolution analysis (TMRA) framework was extended by first using SVM (Supported Vector Machines) classify the video frames within a sliding window into normal frames, gradual transition frames and CUT frames, then clustering the classified frames into different shot categories. The experimental result on ground truth, which has about 26 hours (13,344 shots) news video clips, shows that the new framework has relatively good accuracy for the detection of shot boundaries. It basically solves the difficulties of shot boundaries detection caused by sub-window technique in video. The framework also greatly improves the accuracy of gradual transitions.