Authentication-Based on Biomechanics of Finger Movements Captured Using Optical Motion-Capture

In this paper, we propose an authentication approach based on the uniqueness of the biomechanics of finger movements. We use an optical-marker-based motion-capture as a preliminary setup to capture goniometric (joint-related) and dermatologic (skin-related) features from the flexion and extension of the index and middle fingers of a subject. We use this information to build a personalized authentication model for a given subject. Analysis of our approach using finger motion-capture from 8 subjects, using reflective tracking markers placed around the joints of index and middle fingers of the subjects shows its viability. In this preliminary study, we achieve an average equal error rate (EER)-when false accept rate and false reject rate are equal-of 6.3% in authenticating a subject immediately after training the authentication model and 16.4% ERR after a week.