Abstract
We present a novel approach to liveness verification based on visual speech recognition within a challenge-based framework which has the potential to be used on mobile devices to prevent replay or spoof attacks during Face-based liveness verification. The system uses model visual speech recognition and determines liveness based on the Levenshtein Distance between a randomly generated challenge phrase and the hypothesis utterances from the visual speech recognizer. A Deep learning-based approach to visual speech recognition is used to improve upon the state of the art for the use of visual speech recognition for liveness verification.
Original language | English |
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Title of host publication | 12th International Conference for Internet Technology and Secured Transactions (ICITST 2017): Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 405-410 |
Number of pages | 6 |
ISBN (Electronic) | 9781908320933 |
DOIs | |
Publication status | Published - 10 May 2018 |
Event | 12th International Conference for Internet Technology and Secured Transactions, ICITST 2017 - Cambridge, United Kingdom Duration: 11 Dec 2017 → 14 Dec 2017 |
Conference
Conference | 12th International Conference for Internet Technology and Secured Transactions, ICITST 2017 |
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Country/Territory | United Kingdom |
City | Cambridge |
Period | 11/12/2017 → 14/12/2017 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
- Safety, Risk, Reliability and Quality
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Dive into the research topics of 'Challenge based visual speech recognition using deep learning'. Together they form a unique fingerprint.Student Theses
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Visual speech recognition in sparse data domains
Author: McShane, P., Dec 2022Supervisor: Stewart, D. (Supervisor) & Ji, M. (Supervisor)
Student thesis: Doctoral Thesis › Doctor of Philosophy
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