Abstract
This study addresses the camera placement problem for bridge surveillance and proposes solutions that minimize the cost while satisfying the minimum coverage level. We discuss the field of view of cameras in the three-dimensional space. We also consider occlusions, the characteristics of surveillance targets, and different pan-tilt-zoom cameras in the visibility test. To solve the camera placement problem while minimizing the total cost, we propose a genetic algorithm (GA) and a uniqueness score with a local search algorithm (ULA). Problem sets for a large-scale dimension scenario are generated based on the data of actual bridges in the Republic of Korea. For three simulation sets and a case study of Samoonjin Bridge, the proposed ULA yields better results than GA.
Highlights
The increasing social demand for disaster-recovery systems has resulted in an increasing requirement for surveillance activities in core-infrastructure components
The remainder of this manuscript is organized as follows: In Section 2, we review previous research related to camera placement problems; in Section 3, we describe the characteristics of the camera placement problem with the help of basic definitions and assumptions; in Section 4, we present three heuristic algorithms to solve the defined problem; in Section 5, we describe experiments conducted to verify the validity of our approach and summarize the experimental results; and in Section 6, we present the conclusion and discuss possible extensions of our study
The camera placement problem is closely related to the art gallery problem (AGP), which is the problem of determining the minimum number of guards required to cover the interior of an art gallery [5]
Summary
The increasing social demand for disaster-recovery systems has resulted in an increasing requirement for surveillance activities in core-infrastructure components. In the case of placing cameras to monitor large infrastructures, the size of the problem and the number of decision variables increase as the number of feasible locations for the camera and the number of grid points increase due to the nature of the NP-hard problem To address this issue, we present the visibility test with a minimum coverage level to efficiently reduce the search space. The occluded view of the camera, the restricted areas, and the broader field of view of the PTZ cameras result in an increased computation time and memory usage for the camera placement problem due to the higher number of possible configurations, overlapped areas, and occluded points Considering these constraints and developing algorithms to arrive at the efficient placement of cameras within a reasonable timeframe constitutes a significant step toward increasing the scope of applications in the field. The remainder of this manuscript is organized as follows: In Section 2, we review previous research related to camera placement problems; in Section 3, we describe the characteristics of the camera placement problem with the help of basic definitions and assumptions; in Section 4, we present three heuristic algorithms to solve the defined problem; in Section 5, we describe experiments conducted to verify the validity of our approach and summarize the experimental results; and in Section 6, we present the conclusion and discuss possible extensions of our study
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