DocumentCode :
1688923
Title :
An Ontology for Event Detection and its Application in Surveillance Video
Author :
SanMiguel, Juan Carlos ; Martínez, José M. ; García, Álvaro
Author_Institution :
Video Process. & Understanding Lab., Univ. Autonoma de Madrid, Madrid, Spain
fYear :
2009
Firstpage :
220
Lastpage :
225
Abstract :
In this paper, we propose an ontology for representing the prior knowledge related to video event analysis. It is composed of two types of knowledge related to the application domain and the analysis system. Domain knowledge involves all the high level semantic concepts in the context of each examined domain (objects, events, context...) whilst system knowledge involves the capabilities of the analysis system (algorithms, reactions to events...). The proposed ontology has been structured in two parts: the basic ontology (composed of the basic concepts and their specializations) and the domain-specific extensions. Additionally, a video analysis framework based on the proposed ontology is defined for the analysis of different application domains showing the potential use of the proposed ontology. In order to show the real applicability of the proposed ontology, it is specialized for the underground video-surveillance domain showing some results that demonstrate the usability and effectiveness of the proposed ontology.
Keywords :
knowledge representation; object detection; ontologies (artificial intelligence); video surveillance; event detection; knowledge representation; ontology; underground video-surveillance domain; video event analysis; Algorithm design and analysis; Event detection; Knowledge representation; Layout; Logic; Object detection; Ontologies; Proposals; Resource description framework; Surveillance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Video and Signal Based Surveillance, 2009. AVSS '09. Sixth IEEE International Conference on
Conference_Location :
Genova
Print_ISBN :
978-1-4244-4755-8
Electronic_ISBN :
978-0-7695-3718-4
Type :
conf
DOI :
10.1109/AVSS.2009.28
Filename :
5279823
Link To Document :
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