The use of visual sensors is flourishing, driven among others by the several applications in detection and prevention of crimes or dangerous events. While the problem of optimal camera placement for total coverage has been solved for a decade or so, that of the arrangement of cameras maximizing the recognition of objects "in-transit" is still open. The objective of this paper is to attack this problem by providing an adversarial method of proven optimality based on the resolution of Hamilton-Jacobi equations. The problem is attacked by first assuming the perspective of an adversary, i.e. computing explicitly the path minimizing the probability of detection and the quality of reconstruction. Building on this result, we introduce an optimality measure for camera configurations and perform a simulated annealing algorithm to find the optimal camera placement.

翻译：视觉传感器的应用正在蓬勃发展，这主要得益于其在犯罪或危险事件检测与预防中的多种用途。尽管全面覆盖的最优摄像机放置问题大约在十年前就已解决，但如何布置摄像机以最大化对“运输途中”物体的识别能力这一问题仍然悬而未决。本文旨在通过提供一种基于Hamilton-Jacobi方程求解的、具有可证明最优性的对抗性方法来攻克这一难题。我们首先从对抗者的视角出发，即显式计算能够最小化被检测概率与重建质量的路径。基于这一结果，我们引入了摄像机配置的最优性度量，并采用模拟退火算法来寻找最优的摄像机布局位置。