Automatic partitioning of full-motion video
Multimedia Systems
Video parsing and browsing using compressed data
Multimedia Tools and Applications
Automatic video data structuring through shot partitioning and key-frame computing
Machine Vision and Applications
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 and cost-effective techniques for browsing and indexing large video databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Determining computable scenes in films and their structures using audio-visual memory models
MULTIMEDIA '00 Proceedings of the eighth ACM international conference on Multimedia
Constructing table-of-content for videos
Multimedia Systems - Special section on video libraries
Efficient matching and clustering of video shots
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
Key frame selection by motion analysis
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
Time-Constrained Keyframe Selection Technique
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Rapid scene analysis on compressed video
IEEE Transactions on Circuits and Systems for Video Technology
Automated high-level movie segmentation for advanced video-retrieval systems
IEEE Transactions on Circuits and Systems for Video Technology
Associating characters with events in films
Proceedings of the 6th ACM international conference on Image and video retrieval
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Automatic video segmentation is the first and necessary step for organizing a long video file into several smaller units for subsequent browsing and retrieval. The smallest basic unit is shot. Since users of a video database management system are more likely to recall important events or stories rather than a particular frame or shot, relevant shots are typically grouped into a high-level unit called scene. Each scene is part of a story. Browsing these scenes unfolds the entire story of the film, allowing the users to locate their desired video segments quickly and efficiently. Existing scene definitions are rather broad, making it difficult to evaluate the scene results and compare existing techniques. This paper first gives a stricter scene definition and presents ShotWeave, a novel technique for clustering relevant shots into a scene for narrative films. The crux of Shot Weave is its feature extraction and comparison. Features are extracted from carefully selected regions of representative frames of shots. These regions capture essential information needed to maintain viewers' thought in presence of shot breaks guided by common continuity-editing techniques used in film making. The experimental results show that ShotWeave performs well, and is more robust than a recent shot clustering technique on full-length films consisting of a wide range of camera motions and a complex composition of related shots.