Decision Combination in Multiple Classifier Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
An efficient video segmentation scheme for MPEG video stream using macroblock information
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Efficient MPEG compressed video analysis using macroblock typeinformation
IEEE Transactions on Multimedia
Fast scene change detection using direct feature extraction fromMPEG compressed videos
IEEE Transactions on Multimedia
Computational similarity based on chromatic barycenter algorithm
IEEE Transactions on Consumer Electronics
Rapid scene analysis on compressed video
IEEE Transactions on Circuits and Systems for Video Technology
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In this paper we propose a method to detect abrupt shot changes in MPEG coded videos that operates directly on the compressed domain by using a Multi-Expert approach. Generally, costly analysis for addressing the weakness of a single expert for abrupt shot change detection and the consequent modifications would produce only slight performance improvements. Hence, after a careful analysis of the scientific literature, we selected three techniques for cut detection, which extract complementary features and operate directly in the compressed domain. Then, we combined them into different kinds of Multi-Expert Systems (MES) employing three combination rules: Majority Voting, Weighted Voting and Bayesian rule. In order to assess the performance of the proposed MES, we built up a huge database, much wider than those used in the field. Experimental results demonstrate that the proposed system performs better than each of the three single algorithms.