Universal coalgebra: a theory of systems
Theoretical Computer Science - Modern algebra and its applications
In defence of the 8-point algorithm
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Mathematical Models of Interactive Computing
Mathematical Models of Interactive Computing
A Shortest Path Representation for Video Summarisation
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
A new general framework for shot boundary detection and key-frame extraction
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Two-stage hierarchical video summary extraction to match low-level user browsing preferences
IEEE Transactions on Multimedia
Rapid estimation of camera motion from compressed video with application to video annotation
IEEE Transactions on Circuits and Systems for Video Technology
A novel video key-frame-extraction algorithm based on perceived motion energy model
IEEE Transactions on Circuits and Systems for Video Technology
Key frame vector and its application to shot retrieval
IMCE '09 Proceedings of the 1st international workshop on Interactive multimedia for consumer electronics
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
A design-of-experiment based statistical technique for detection of key-frames
Multimedia Tools and Applications
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Video summarization can provide a fine representation of the content of video stream and reduce a large amount of data involved in video indexing, browsing, and retrieval. Moreover, Key frame selection is an important step in the research of content-based video analysis and retrieval. Although there exist a variety of methods for key frame selection, they are heuristic and closed systems, which cannot dynamically generate video summary with user's preference. In this paper, an M-estimator and epipolar line distance constraint camera motion estimation algorithm is introduced as camera parameters is an important motion feature for key frame selection, and Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is applied to optimize estimated parameters. Moreover, since Interactive Computing is a novel-computing model that represents the transition of algorithm to interaction, an interactive model of key frame selection (IKFS) is presented as a result of improving the model of key frame selection (KFS). The model of KFS and IKFS are proved to satisfy the criterion of induction and coinduction, respectively. Experimental results show that the processing scheme generates flexible and desirable summarizations whose distortion rate is lower than current method. Above all, IKFS is an extension to KFS.