Cobra: A Content-Based Video Retrieval System
An increasing number of large publicly available video libraries results in a demand for techniques that can manipulate the video data based on content. In this paper, we present a content-based video retrieval system called Cobra. The system supports automatic extraction and retrieval of high-level concepts (such as video objects and events) from raw video data. It benefits from using domain knowledge,but at the same time,pro vides a general framework that can be used in different domains.
The contribution of this work is twofold. Firstly, we demonstrate how different knowledge-based techniques can be used together within a single video database management system to interpret low-level video features into semantic content. The system uses spatio-temporal rules,Hidden Markov Models (HMMs),and Dynamic Bayesian Networks (DBNs) to model and recognize video objects and events. Secondly,w e show how these techniques can be effectively used for different application domains. In particular, we validate our approach in the domain of tennis and Formula 1 videos.
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- 1.P. Boncz, A.N. Wilschut, M.L. Kersten. Flattering an object algebra to provide performance. In Proc. IEEE Intl. Conf. on Data Engineering, pages 568–577, 1998.Google Scholar
- 2.M. Petković, W. Jonker. Content-Based Video Retrieval by Integrating Spatio-Temporal and Stochastic Recognition of Events. In Proc. IEEE International Workshop on Detection and Recognition of Events in Video, pages 75–82, 2001.Google Scholar
- 3.V. Mihajlović, M. Petković. Automatic Annotation of Formula 1R aces for Content-Based Video Retrieval, CTIT Technical Report, TR-CTIT-01-41, 2001.Google Scholar