Abstract
Covert surveillance devices ranging from miniature cameras to voice recorders are increasingly affordable and accessible on the market, raising concerns about surreptitious and unauthorized observation of people. This article contributes an innovative method for discovering covert surveillance devices using thermal imaging integrated with off-the-shelf consumer devices, such as smartphones. We develop a simple yet efficient processing pipeline for identifying covert devices and demonstrate its effectiveness through extensive and systematic evaluations that consider different types of covert cameras. Our results show robustness against a wide range of factors, including distance to other electrical objects, the environment and luminosity of the space where measurements are taken, the type of camera, and partial occlusion of the hidden devices.
Agustin Zuniga
Pervasive Data Science group
Dr. Agustin Zuniga works in the areas of pervasive data science and artificial intelligence of things, especially in low-cost sensing and intelligent sensing pipeline solutions.