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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Gomez-Romero, J. Patricio, M.A. Garcia, J. Molina, J.M. |
| Copyright Year | 2009 |
| Abstract | Classical tracking methods are often insufficient when dealing with complex scenarios. In order to solve tracking errors, innovative techniques based on the use of information about the context of the scene have been proposed. Context information ranges from precise measures computed on the pixels of the object neighborhood to high level representations of the entities and the activities of the scene. In this work, we focus on the second approach and propose an ontology-based extension of a general tracking procedure that reasons with abstract context descriptions to improve its accuracy. We describe the design of this extension and how reasoning is performed, as well as its advantages in surveillance scenarios. |
| Starting Page | 226 |
| Ending Page | 231 |
| File Size | 440593 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424447558 |
| DOI | 10.1109/AVSS.2009.21 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-09-02 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computer vision OWL Ontologies Application software Surveillance automatic reasoning Layout Lighting Computer errors context object tracking Labeling Artificial intelligence ontologies |
| Content Type | Text |
| Resource Type | Article |
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