| 1. |
- Alqaysi, Hiba, et al.
(author)
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Evaluating Coverage Effectiveness of Multi-Camera Domes Placement for Volumetric Surveillance
- 2017
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In: ICDSC 2017 Proceedings of the 11th International Conference on Distributed Smart Cameras. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450354875 ; , s. 49-54
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Conference paper (peer-reviewed)abstract
- Multi-camera dome is composed of a number of cameras arranged to monitor a half sphere of the sky. Designing a network of multi-camera domes can be used to monitor flying activities in open large area, such as birds' activities in wind parks. In this paper, we present a method for evaluating the coverage effectiveness of the multi-camera domes placement in such areas. We used GPS trajectories of free flying birds over an area of 9 km2 to analyze coverage effectiveness of randomly placed domes. The analysis is based on three criteria namely, detection, positioning and the maximum resolution captured. The developed method can be used to evaluate results of designing and optimizing dome placement algorithms for volumetric monitoring systems in order to achieve maximum coverage.
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| 2. |
- Fedorov, Igor, et al.
(author)
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Placement Strategy of Multi-Camera Volumetric Surveillance System for Activities Monitoring
- 2017
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In: ICDSC 2017 Proceedings of the 11th International Conference on Distributed Smart Cameras. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450354875 ; , s. 113-118
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Conference paper (peer-reviewed)abstract
- The design of multi-camera surveillance system comes with many advantages, for example it facilitates as understanding how flying objects act in a given volume. One possible application is for the observation interaction of birds and calculate their trajectories around wind turbines to create promising systems for preventing bird collisions with turbine blades. However, there are also challenges, such as finding the optimal node placement and camera calibration. To address these challenges we investigated a trade-off between calibration accuracy and node requirements, including resolution, modulation transfer function, field of view and angle baseline. We developed a strategy for camera placement to achieve improved coverage for golden eagle monitoring and tracking. This strategy based on the modified resolution criterion taking into account the contrast function of the camera and the estimation of the base angle between the cameras.
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| 3. |
- Shallari, Irida, et al.
(author)
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Evaluating Pre-Processing Pipelines for Thermal-Visual Smart Camera
- 2017
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In: Proceedings of the 11th International Conference on Distributed Smart Cameras. - New York, NY, USA : ACM Digital Library. - 9781450354875 ; , s. 95-100
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Conference paper (peer-reviewed)abstract
- Smart camera systems integrating multi-model image sensors provide better spectral sensitivity and hence better pass-fail decisions. In a given vision system, pre-processing tasks have a ripple effect on output data and pass-fail decision of high level tasks such as feature extraction, classification and recognition. In this work, we investigated four pre-processing pipelines and evaluated the effect on classification accuracy and output transmission data. The pre-processing pipelines processed four types of images, thermal grayscale, thermal binary, visual and visual binary. The results show that the pre-processing pipeline, which transmits visual compressed Region of Interest (ROI) images, offers 13 to 64 percent better classification accuracy as compared to thermal grayscale, thermal binary and visual binary. The results show that visual raw and visual compressed ROI with suitable quantization matrix offers similar classification accuracy but visual compressed ROI offers up to 99 percent reduced communication data as compared to visual ROI.
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