NSF workshop on Visual Information Management Systems
ACM SIGMOD Record
ACM SIGMOD Record
Towards a semantic image database system
Data & Knowledge Engineering
VideoQ: an automated content based video search system using visual cues
MULTIMEDIA '97 Proceedings of the fifth ACM international conference on Multimedia
Automatic video data structuring through shot partitioning and key-frame computing
Machine Vision and Applications
VIMS: A Video Information Management System
Multimedia Tools and Applications
OVID: Design and Implementation of a Video-Object Database System
IEEE Transactions on Knowledge and Data Engineering
Constructing table-of-content for videos
Multimedia Systems - Special section on video libraries
Using Adaptive Tracking to Classify and Monitor Activities in a Site
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A High-Level Semantics Extraction Model for Stored Videos
MSE '00 Proceedings of the 2000 International Conference on Microelectronic Systems Education
Time-Constrained Clustering for Segmentation of Video into Story Unites
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Extracting story units from long programs for video browsing and navigation
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Video query: research directions
IBM Journal of Research and Development - Papers on mustimedia systems
BilVideo: Design and Implementation of a Video Database Management System
Multimedia Tools and Applications
Visual video retrieval system using MPEG-7 descriptors
Proceedings of the Third International Conference on SImilarity Search and APplications
SHIATSU: tagging and retrieving videos without worries
Multimedia Tools and Applications
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Digital video databases have become more pervasive and finding video clips quickly in large databases becomes a major challenge. Due to the nature of video, accessing contents of video is difficult and time-consuming. With content-based video systems today, there exists a significant gap between the user's information and what the system can deliver. Therefore, enabling intelligent means of interpretation on visual content, semantics annotation and retrieval are important topics of research. In this paper, we consider semantic interpretation of the contents as annotation tags for video clips, giving a retrieval-driven and application-oriented semantics extraction, annotation and retrieval model for video database management system. This system design employs an algorithm on objects' relation and it can reveal the semantics defined with fast real-time computation.