Hierarchical Shot Clustering for Video Summarization
ICCS '02 Proceedings of the International Conference on Computational Science-Part III
Automatic Scene Detection in News Program by Integrating Visual Feature and Rules
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Key-frame extraction algorithm using entropy difference
Proceedings of the 6th ACM SIGMM international workshop on Multimedia information retrieval
Modeling human color categorization
Pattern Recognition Letters
Normalized Cut Based Coherence Measure Construction for Scene Segmentation
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Generation of size constrained video storyboard using spanning tree
Proceedings of the First International Conference on Internet Multimedia Computing and Service
Scene pathfinder: unsupervised clustering techniques for movie scenes extraction
Multimedia Tools and Applications
A novel video thumbnail extraction method using spatiotemporal vector quantization
Proceedings of the 3rd international workshop on Automated information extraction in media production
Proceedings of the 2010 ACM workshop on Social, adaptive and personalized multimedia interaction and access
Parallel-sequential texture analysis
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Video scene segmentation using time constraint dominant-set clustering
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Video shot representation based on histograms
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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For more efficient organizing, browsing, and retrieving digital video content, it is important to extract video structure information at both scene and shot levels. This paper presents an effective approach to video scene segmentation based on a pseudo-object-based shot correlation analysis. A new measure of the semantic correlation of consecutive shots based on dominant color grouping and tracking is proposed. A new shot grouping method named expanding window is designed to cluster correlated consecutive shots into one scene. Evaluations based on real-world sports video programs validate the efficiency and effectiveness of our shot correlation measure and scene structure construction.