Two-Phase Algorithm for Optimal Camera Placement

Abstract

As markers for visual sensor networks have become larger, interest in the optimal camera placement problem has continued to increase. The most featured solution for the optimal camera placement problem is based on binary integer programming (BIP). Due to the NP-hard characteristic of the optimal camera placement problem, however, it is difficult to find a solution for a complex, real-world problem using BIP. Many approximation algorithms have been developed to solve this problem. In this paper, a two-phase algorithm is proposed as an approximation algorithm based on BIP that can solve the optimal camera placement problem for a placement space larger than in current studies. This study solves the problem in three-dimensional space for a real-world structure.

Systematic Camera Placement Framework for Operation-Level Visual Monitoring on Construction Jobsites

“…problems (Ahn et al 2016), future studies can focus on investigating algorithmic enhancement (e.g., parameter tuning) to avoid being stuck at a local optimum. In contrast, the current semiautomated jobsite modeling involves a manual process by project managers.…”

“…The AGP originated from the challenges in determining the minimal number of guards and their locations required to cover the interior of an art gallery (Hörster and Lienhart 2006). Because general camera placement problems are similar to the AGP (Ahn et al 2016;Hörster and Lienhart 2006), AGP theorems and algorithms have been studied to find the optimal camera placement in various domains.…”

“…Omnidirectional and pan-tilt-zoom (PTZ) cameras were also considered for coverage modeling and maximization problems (Altahir et al 2017;Gonzalez-Barbosa et al 2009;Indu et al 2009). Recently, the camera placement problems have been extended to multiobjective optimization that not only maximizes cameras' coverage but also minimizes investment costs (Ahn et al 2016;Altahir et al 2017;Zhao et al 2013). To solve the defined problems with a reasonable practical range of accuracy, researchers have also tested the applicability of metaheuristic optimization algorithms for camera placement (Abdesselam and Baarir 2018;Aissaoui et al 2017;Al-Hmouz and Challa 2005).…”

Coverage Aware Scheduling Strategies for 3D Wireless Video Sensor Nodes to Enhance Network Lifetime

“…But as all VSNs in the target area stay awake both in [19], [21], there still exists a lot of wastage of energy and redundancy in visual data. A two-phase algorithm has been proposed in [22] as an algorithm based on Binary Integer Programming that can solve the optimal camera placement problem for a placement space larger than in the current study. This study solves the problem in three-dimensional space for a real-world structure.…”

“…A binary particle swarm optimization algorithm to solve a homogeneous planned camera network placement problem has been provided in [23]. But both [22], [23] deal with planned deployment of VSNs in the target area which is not possible in the post-disaster scenario.…”