A smart environment for biometric capture

Abstract

Current biometric capture methodologies were born in a laboratory environment. In this scenario you have cooperative subjects, large time capture windows, and staff to edit and mark up data as necessary. However, as biometrics moves from the laboratory these factors impinge upon the scalability of the system. In this work we developed a prototype biometric tunnel for the capture of non-contact biometrics. The system is autonomous to maximise subject throughput and self-contained to allow flexible deployment and user friendliness. Currently we deploy 8 cameras to capture the 3D motion (specifically gait) and 1 camera to capture the face of a subject. The gait and face information thus extracted can be used for subsequent biometric analysis. Interaction between the various system components is performed via the use of an agent framework. Performance analysis of the current system shows that we can currently achieve a moderate throughput of 15 subjects per hour. Additionally, analysis performed upon the biometric features extracted from a small population show them to be potent for recognition