Fusion of Face Recognition Algorithms for Video-Based Surveillance Systems
Publication Type:Book Chapter
Source:Multisensor Surveillance Systems: The Fusion Perspective, Kluwer Academic, p.235-250 (2003)
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. Unfortunately, face recognition algorithms showed to suffer a lot from the high variability of environmental conditions (e.g., variations of lighting, face pose and scale). This currently limits their application to real video-surveillance tasks. Recently, fusion of multiple face recognisers has been proposed to improve the robustness of face recognition systems to environmental conditions variability. In this chapter, fusion of two well-known face recognition algorithms, namely, PCA and LDA, is proposed. Experimental results that confirm the benefits of fusing PCA and LDA allow drawing some preliminary conclusions about the role of the fusion of face recognition algorithms in video-based surveillance applications.