Gait template protection using HMM-UBM

© 2018 Gesellschaft fuer Informatik. This paper presents a hidden Markov model-Universal background model gait authentication system, which is also incorporated into a template protection based on a fuzzy commitment scheme. We show that with limited enrollment data the HMM-UBM system achieves a very competitive equal error rate of ≈ 1% using one sensor. The proposed template protection scheme benefits from eigenfeatures coming from multiple Universal background model systems fused with a novel technique that minimizes the bit error rate for genuine attempts. This allows the protected system to achieve a false rejection rate below 5% with an effective key length of 64 bits.

ISBN:978-3-88579-676-3

Publication year:2018

BOF-keylabel:yes

IOF-keylabel:yes

Authors from:Higher Education

Accessibility:Closed