Video parsing, retrieval and browsing: an integrated and content-based solution
Proceedings of the third ACM international conference on Multimedia
Segmentation of video by clustering and graph analysis
Computer Vision and Image Understanding
A stochastic framework for optimal key frame extraction from MPEG video databases
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Key-frame extraction and shot retrieval using nearest feature line (NFL)
MULTIMEDIA '00 Proceedings of the 2000 ACM workshops on Multimedia
Motion-Based Video Representation for Scene Change Detection
International Journal of Computer Vision
Statistical Learning of Multi-view Face Detection
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Video Summaries through Mosaic-Based Shot and Scene Clustering
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Constructing table-of-content for videos
Multimedia Systems - Special section on video libraries
Video Scene Segmentation via Continuous Video Coherence
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A feature-based algorithm for detecting and classifying production effects
Multimedia Systems
Content-based retrieval of video data by the grammar of film
VL '97 Proceedings of the 1997 IEEE Symposium on Visual Languages (VL '97)
Highlight scene extraction in real time from baseball live video
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Structure analysis of soccer video with domain knowledge and hidden Markov models
Pattern Recognition Letters - Video computing
Supervised classification for video shot segmentation
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Video shot segmentation using singular value decomposition
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - 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
Scene Determination Based on Video and Audio Features
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Graph partition model for robust temporal data segmentation
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Shot clustering techniques for story browsing
IEEE Transactions on Multimedia
Detection and representation of scenes in videos
IEEE Transactions on Multimedia
Video scene segmentation using Markov chain Monte Carlo
IEEE Transactions on Multimedia
Automated high-level movie segmentation for advanced video-retrieval systems
IEEE Transactions on Circuits and Systems for Video Technology
Scene extraction in motion pictures
IEEE Transactions on Circuits and Systems for Video Technology
Toward a conceptual framework of key-frame extraction and storyboard display for video summarization
Journal of the American Society for Information Science and Technology
A heuristic algorithm for video scene detection using shot cluster sequence analysis
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
A template-based baseball video scene classification using efficient playfield segmentation
Multimedia Tools and Applications
High level video temporal segmentation
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Video Segmentation and Structuring for Indexing Applications
International Journal of Multimedia Data Engineering & Management
Bag of visual words model for videos segmentation into scenes
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
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Grouping video content into semantic segments and classifying semantic scenes into different types are the crucial processes to content-based video organization, management and retrieval. In this paper, a novel approach to automatically segment scenes and semantically represent scenes is proposed. Firstly, video shots are detected using a rough-to-fine algorithm. Secondly, key-frames within each shot are selected adaptively with hybrid features, and redundant key-frames are removed by template matching. Thirdly, spatio-temporal coherent shots are clustered into the same scene based on the temporal constraint of video content and visual similarity between shot activities. Finally, under the full analysis of typical characters on continuously recorded videos, scene content is semantically represented to satisfy human demand on video retrieval. The proposed algorithm has been performed on various genres of films and TV program. Promising experimental results show that the proposed method makes sense to efficient retrieval of interesting video content.