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Solution space expl...
Solution space exploration of volumetric surveillance using a general taxonomy
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- Ahmad, Naeem (author)
- Mittuniversitetet,Avdelningen för elektronikkonstruktion
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- Imran, Muhammad (author)
- Mittuniversitetet,Avdelningen för elektronikkonstruktion
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- Khursheed, Khursheed (author)
- Mittuniversitetet,Avdelningen för elektronikkonstruktion
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- Lawal, Najeem (author)
- Mittuniversitetet,Avdelningen för elektronikkonstruktion
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- O'Nils, Mattias (author)
- Mittuniversitetet,Avdelningen för elektronikkonstruktion
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(creator_code:org_t)
- SPIE, 2013
- 2013
- English.
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In: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE. - 9780819495044 ; , s. Art. no. 871317-
- Related links:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Subject headings
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- Visual surveillance systems provide real time monitoring of the events or the environment. The availability of low cost sensors and processors has increased the number of possible applications of these kinds of systems. However, designing an optimized visual surveillance system for a given application is a challenging task, which often becomes a unique design task for each system. Moreover, the choice of components for a given surveillance application out of a wide spectrum of available alternatives is not an easy job. In this paper, we propose to use a general surveillance taxonomy as a base to structure the analysis and development of surveillance systems. We demonstrate the proposed taxonomy for designing a volumetric surveillance system for monitoring the movement of eagles in wind parks aiming to avoid their collision with wind mills. The analysis of the problem is performed based on taxonomy and behavioral and implementation models are identified to formulate the solution space for the problem. Moreover, we show that there is a need for generalized volumetric optimization methods for camera deployment.
Keyword
- Taxonomy; surveillance; coverage; visual sensor network
Publication and Content Type
- ref (subject category)
- kon (subject category)
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