Automatic partitioning of full-motion video
Multimedia Systems
Quality is in the eye of the beholder: meeting users' requirements for Internet quality of service
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Using string matching to detect video transitions
Pattern Analysis & Applications
Making colors worth more than a thousand words
Proceedings of the 2008 ACM symposium on Applied computing
Robust Estimation of Camera Motion Using Optical Flow Models
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
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
Rapid scene analysis on compressed video
IEEE Transactions on Circuits and Systems for Video Technology
Shot-boundary detection: unraveled and resolved?
IEEE Transactions on Circuits and Systems for Video Technology
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The temporal segmentation of a video sequence is one of the most important aspects for video processing, analysis, indexing, and retrieval. Most of existing techniques to address the problem of identifying the boundary between consecutive shots have focused on the uncompressed domain. However, decoding and analyzing of a video sequence are two extremely time-consuming tasks. Since video data are usually available in compressed form, it is desirable to directly process video material without decoding. In this paper, we present a novel approach for video cut detection that works in the compressed domain. The proposed method is based on both exploiting visual features extracted from the video stream and on using a simple and fast algorithm to detect the video transitions. Experiments on a real-world video dataset with several genres show that our approach presents high accuracy relative to the state-of-the-art solutions and in a computational time that makes it suitable for online usage.