Biometric Recognition in Surveillance Environments Using Master-Slave Architectures

The number of visual surveillance systems deployed worldwide has been growing astoundingly. As a result, attempts have been made to increase the levels of automated analysis of such systems, towards the reliable recognition of human beings in fully covert conditions. Among other possibilities, master-slave architectures can be used to acquire high resolution data of subjects heads from large distances, with enough resolution to perform face recognition. This paper/tutorial provides a compre-hensive overview of the major phases behind the development of a recognition system working in outdoor surveillance scenarios, describing frameworks and methods to: 1) use coupled wide view and Pan-Tilt-Zoom (PTZ) imaging devices in surveillance settings, with a wide-view camera covering the whole scene, while a synchronized PTZ device collects high-resolution data from the head region; 2) use soft biometric information (e.g., body metrology and gait) for pruning the set of potential identities for each query; and 3) faithfully balance ethics/privacy and safety/security issues in this kind of systems.