Abstract
This paper investigated using lip movements as a behavioural biometric for person authentication. The system was trained, evaluated and tested using the XM2VTS dataset, following the Lausanne Protocol configuration II. Features were selected from the DCT coefficients of the greyscale lip image. This paper investigated the number of DCT coefficients selected, the selection process, and static and dynamic feature combinations. Using a Gaussian Mixture Model - Universal Background Model framework an Equal Error Rate of 2.20% was achieved during evaluation and on an unseen test set a False Acceptance Rate of 1.7% and False Rejection Rate of 3.0% was achieved. This compares favourably with face authentication results on the same dataset whilst not being susceptible to spoofing attacks.
Original language | English |
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Title of host publication | Irish Machine Vision & Image Processing Conference Proceedings 2015 |
Editors | Rozenn Dahyot, Gerard Lacey, Kenneth Dawson-Howe, François Pitié, David Moloney |
Publisher | Irish Pattern Recognition & Classification Society |
Pages | 11-18 |
Number of pages | 8 |
ISBN (Print) | 9780993420702 |
Publication status | Published - 2015 |
Event | Irish Machine Vision and Image Processing Conference 2015 - Trinity College, Dublin, Ireland Duration: 26 Aug 2015 → 28 Aug 2015 |
Conference
Conference | Irish Machine Vision and Image Processing Conference 2015 |
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Country/Territory | Ireland |
City | Dublin |
Period | 26/08/2015 → 28/08/2015 |
Bibliographical note
Winner of Best Student Paper AwardKeywords
- Authentication
- Biometrics
- DCT
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
Fingerprint
Dive into the research topics of 'Investigation into DCT Feature Selection for Visual Lip-Based Biometric Authentication'. Together they form a unique fingerprint.Student theses
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Lip-based biometric authentication
Wright, C. (Author), Stewart, D. (Supervisor), Dec 2019Student thesis: Doctoral Thesis › Doctor of Philosophy
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