A video retrieval and sequencing system
ACM Transactions on Information Systems (TOIS) - Special issue on video information retrieval
Modeling Content for Semantic-Level Querying of Multimedia
Multimedia Tools and Applications
A Database Approach for Modeling and Querying Video Data
IEEE Transactions on Knowledge and Data Engineering
Modelling and Querying Video Data
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
The Stratification System - A Design Emvironment for Random Access
Proceedings of the Third International Workshop on Network and Operating System Support for Digital Audio and Video
Semantic Video Model for Content-Based Retrieval
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
A Semantic Modeling Approach for Video Retrieval by Content
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Motion and Color-Based Video Indexing and Retrieval
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
A Database Approach for Modeling and Querying Video Data
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Video / Text Linkage System Assisted by a Concept Dictionary and Image Recognitio
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
ICMCS '97 Proceedings of the 1997 International Conference on Multimedia Computing and Systems
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In this paper, a semantic video retrieval system is proposed based on the stories of the videos. A hierarchical knowledge model is used to express the semantic meanings contained in the videos, and a video query language is also provided. The terms of Object, Action and Relation are used to specify rich and complex semantic meanings in a query. Based on the proposed knowledge model, the retrieval system is able to make inferences on the terms appearing in a query, and determine whether a video semantically matches the query conditions. The semantic similarity measurement is also proposed for processing approximate queries.