Facial Surveillance and Recognition in the Passive Infrared Bands

Abstract

This chapter discusses the use of infrared imaging to perform surveillance and recognition where the face is used for recognizing individuals. In particular, it explores properties of the infrared (IR) band, effects of indoor and outdoor illumination on face recognition (FR) and a framework for both homogeneous and heterogeneous FR systems using multi-spectral sensors. The main benefit of mid-wave infrared and long-wave infrared (MWIR, LWIR) camera sensors is the capability to use FR systems when operating in difficult environmental conditions, such as in low light or complete darkness. This allows for the potential to detect and acquire face images of different subjects without actively illuminating the subject, based on their passively emitted thermal signatures. In this chapter, we demonstrate that by utilizing the “passive” infrared band, facial features can be captured irrespective of illumination (e.g. indoor vs. outdoor). For homogeneous FR systems, we formulate and develop an efficient, semi-automated, direct matching-based FR framework, that is designed to operate efficiently when face data is captured using either visible or IR sensors. Thus, it can be applied in both daytime and nighttime environments. The second framework aims to solve the heterogeneous, cross-spectral FR problem, enabling recognition in the MWIR and LWIR bands based on images of subjects in the visible spectrum.