Video abstraction: A systematic review and classification
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Interactive key frame selection model
Journal of Visual Communication and Image Representation
Computational approaches to temporal sampling of video sequences
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
The trecvid 2007 BBC rushes summarization evaluation pilot
Proceedings of the international workshop on TRECVID video summarization
Rushes video summarization by object and event understanding
Proceedings of the international workshop on TRECVID video summarization
Video summarisation: A conceptual framework and survey of the state of the art
Journal of Visual Communication and Image Representation
Video summarization based handout generation from video lectures: a gesture recognition framework
ISCGAV'05 Proceedings of the 5th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision
TVS '08 Proceedings of the 2nd ACM TRECVid Video Summarization Workshop
Summarization scheme based on near-duplicate analysis
TVS '08 Proceedings of the 2nd ACM TRECVid Video Summarization Workshop
Automatic Summarization of Rushes Video Using Bipartite Graphs
SAMT '08 Proceedings of the 3rd International Conference on Semantic and Digital Media Technologies: Semantic Multimedia
Automatic personalized video abstraction for sports videos using metadata
Multimedia Tools and Applications
Bounded coordinate system indexing for real-time video clip search
ACM Transactions on Information Systems (TOIS)
Dynamic video summarization using two-level redundancy detection
Multimedia Tools and Applications
Hierarchical modeling and adaptive clustering for real-time summarization of rush videos
IEEE Transactions on Multimedia
Extracting Key Frames for Surveillance Video Based on Color Spatial Distribution Histograms
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Automatic evaluation method for rushes summary content
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
STIMO: STIll and MOving video storyboard for the web scenario
Multimedia Tools and Applications
Proceedings of the 19th international conference on World wide web
IM(S)2: Interactive movie summarization system
Journal of Visual Communication and Image Representation
Automatic summarization of rushes video using bipartite graphs
Multimedia Tools and Applications
Journal of Visual Communication and Image Representation
Activity-driven content adaptation for effective video summarization
Journal of Visual Communication and Image Representation
Key frame extraction based on visual attention model
Journal of Visual Communication and Image Representation
Generic summarization technology for consumer video
PCM'04 Proceedings of the 5th Pacific Rim Conference on Advances in Multimedia Information Processing - Volume Part II
Automatic evaluation of video summaries
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Advanced Mobile Lecture Viewing: Summarization and Two-Way Navigation
International Journal of Handheld Computing Research
Dynamic video summarization with content analysis
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
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A compact summary of video that conveys visual content at various levels of detail enhances user interaction significantly. In this paper, we propose a two-stage framework to generate MPEG-7-compliant hierarchical key frame summaries of video sequences. At the first stage, which is carried out off-line at the time of content production, fuzzy clustering and data pruning methods are applied to given video segments to obtain a nonredundant set of key frames that comprise the finest level of the hierarchical summary. The number of key frames allocated to each shot or segment is determined dynamically and without user supervision through the use of cluster validation techniques. A coarser summary is generated on-demand in the second stage by reducing the number of key frames to match the low-level browsing preferences of a user. The proposed method has been validated by experimental results on a collection of video programs.