Adversarial Path Planning for Optimal Camera Positioning

TL;DR

This paper introduces an adversarial approach using Hamilton-Jacobi equations to optimize camera placement for better recognition of moving objects, addressing a less-explored aspect of surveillance system design.

Contribution

It presents a novel adversarial method with proven optimality for camera placement that maximizes object recognition during transit, using Hamilton-Jacobi equations and simulated annealing.

Findings

Developed an optimality measure for camera configurations

Implemented a simulated annealing algorithm for placement optimization

Demonstrated improved recognition of moving objects

Abstract

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.