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。尽管针对全覆盖的最优相机布局问题已在大约十年前得到解决，但如何最大化对"行进中"物体识别能力的相机布置方案仍是一个开放性问题。本文旨在通过提出一种基于哈密顿-雅可比方程求解的、具有最优性保证的对抗性方法来攻克这一难题。我们首先从对抗视角切入问题，即显式计算使检测概率与重建质量最小化的路径。基于此结果，我们引入相机配置的最优性度量，并采用模拟退火算法寻找最优相机布局。