Evaluating the Efficiency of a Night-Time, Middle-Range Infrared Sensor for Applications in Human Detection and Recognition

In law enforcement and security applications, the acquisition of face images is critical in producing key trace evidence for the successful identification of potential threats. In this work we, first, use a near infrared (NIR) sensor designed with the capability to acquire images at middle-range stand-off distances at night. Then, we determine the maximum stand-off distance where face recognition techniques can be utilized to efficiently recognize individuals at night at ranges from 30 to approximately 300 ft. The focus of the study is on establishing the maximum capabilities of the mid-range sensor to acquire good quality face images necessary for recognition. For the purpose of this study, a database in the visible (baseline) and NIR spectrum of 103 subjects is assembled and used to illustrate the challenges associated with the problem. In order to perform matching studies, we use multiple face recognition techniques and demonstrate that certain techniques are more robust in terms of recognition performance when using face images acquired at different distances. Experiments show that matching NIR face images at longer ranges (i.e. greater than about 300 feet or 90 meters using our camera system) is a very challenging problem and it requires further investigation.