A NSGA-II based approach for camera placement problem in large scale surveillance application
| Autor: | Kumar Ashis Pati, Venkatesh K Subramanian, Ankit Gupta |
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| Rok vydání: | 2012 |
| Předmět: |
Scale (ratio)
Computer science business.industry media_common.quotation_subject ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Sorting Resolution (logic) Facial recognition system Video tracking Genetic algorithm Range (statistics) Quality (business) Computer vision Artificial intelligence business media_common |
| Zdroj: | 2012 4th International Conference on Intelligent and Advanced Systems (ICIAS2012). |
| DOI: | 10.1109/icias.2012.6306216 |
| Popis: | Camera placement has huge impact on the performance of large scale surveillance. The quality of the coverage and cost of the camera network make the problem multi-objective. The problem becomes even more difficult when realistic conditions like obstacles, preference coverage and resolution are considered. In this work we propose a framework for optimal camera placement, giving simultaneous consideration to different qualitative aspects using multi-objective genetic algorithm (NSGA-II). We improve our camera-coverage model by including the realistic parameters such as frontal coverage and the optimal range of view of a camera. We develop a novel camera coverage calculation algorithm which ensures that the proposed set-up is applicable to surveillance tasks such as face recognition and object tracking. Developed algorithm has been tested on realistic floor plans and optimal lay-outs have been reported. |
| Databáze: | OpenAIRE |
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