A motion based scene tree for browsing and retrieval of compressed videos
Proceedings of the 2nd ACM international workshop on Multimedia databases
Extraction of Film Takes for Cinematic Analysis
Multimedia Tools and Applications
A motion-based scene tree for browsing and retrieval of compressed videos
Information Systems
Movie scene segmentation using background information
Pattern Recognition
International Journal of Intelligent Systems Technologies and Applications
Video scene segmentation and semantic representation using a novel scheme
Multimedia Tools and Applications
A motion-based scene tree for compressed video content management
Image and Vision Computing
Scene pathfinder: unsupervised clustering techniques for movie scenes extraction
Multimedia Tools and Applications
Robust scene boundary detection based on audiovisual information
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Scene boundary detection by audiovisual contents analysis
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Effective video scene detection approach based on cinematic rules
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Robust Video Content Analysis via Transductive Learning
ACM Transactions on Intelligent Systems and Technology (TIST)
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This paper addresses the challenge of bridging the semantic gap between the rich meaning users desire when they query to locate and browse media and the shallowness of media descriptions that can be computed in today's content management systems. To facilitate high-level semantics-based content annotation and interpretation, we tackle the problem of automatic decomposition of motion pictures into meaningful story units, namely scenes. Since a scene is a complicated and subjective concept, we first propose guidelines from film production to determine when a scene change occurs. We then investigate different rules and conventions followed as part of film grammar that would guide and shape an algorithmic solution for determining a scene. Two different techniques using intershot analysis are proposed as solutions in this paper. In addition, we present different refinement mechanisms, such as film-punctuation detection founded on film grammar, to further improve the results. These refinement techniques demonstrate significant improvements in overall performance. Furthermore, we analyze errors in the context of film-production techniques, which offer useful insights into the limitations of our method.