Fusion of Face Recognition Algorithms for Video-Based Surveillance Systems

It is widely acknowledged that face recognition could play an important role in advanced video-based surveillance systems, mainly because it is non intrusive and does not require people cooperation [1–2]. Unfortunately, face recognition algorithms showed to suffer a lot from the high variability of environmental conditions. As an example, the effectiveness of face recognition strongly depends on lighting conditions and on variations in the subject’s pose and expression in front of the camera. This obviously limits their application to real video-surveillance tasks. On the other hand, face is considered a very good biometric. People recognize each other through the face, the acquisition process is non-intrusive, and does not require the collaboration of the subject to be recognized. Therefore, face recognition is a very active research field with many applications. For the purposes of this chapter, the face recognition applications can be subdivided in two types: applications in controlled and uncontrolled environments. One of the main applications of the first type is the so called “identity authentication”. A person submits to the automatic identity verification system its face (frontal and/or profile view) and declares her/his identity. The system matches the acquired face with the “template” stored in its data base, and classifies the person as a “genuine” (i.e., the claimed identity is accepted) or an “impostor”.