The advanced video information system: data structures and query processing
Multimedia Systems
Principles of multimedia database systems
Principles of multimedia database systems
Video summarization by curve simplification
MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Auto-summarization of audio-video presentations
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Rule-based video classification system for basketball video indexing
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Introduction to Algorithms
A user attention model for video summarization
Proceedings of the tenth ACM international conference on Multimedia
OVID: Design and Implementation of a Video-Object Database System
IEEE Transactions on Knowledge and Data Engineering
A probabilistic framework for semantic video indexing, filtering,and retrieval
IEEE Transactions on Multimedia
Summarization of videotaped presentations: automatic analysis of motion and gesture
IEEE Transactions on Circuits and Systems for Video Technology
The priority curve algorithm for video summarization
Information Systems
Story creation from heterogeneous data sources
Multimedia Tools and Applications
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Most past work on video summarization has been based on selecting key frames from videos. We propose a model of video summarization based on three important parameters: Priority (of frames), Continuity (of the summary), and non-Repetition (of the summary). In short, a summary must include high priority frames and must be continuous and non-repetitive. An optimal summary is one that maximizes an objective function based on these three parameters. We show examples of how CPR parameters can be computed and provide algorithms to find optimal summaries based on the CPR approach. Finally, we briefly report on the performance of these algorithms.