Difference between revisions of "Publications:Lip Biometrics for Digit Recognition"
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|PID=239344 | |PID=239344 | ||
− | |Name=Faraj, Maycel I. | + | |Name=Faraj, Maycel I. (mafa) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938));Bigun, Josef (josef) (Högskolan i Halmstad (2804), Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE) (3905), Halmstad Embedded and Intelligent Systems Research (EIS) (3938)) |
|Title=Lip Biometrics for Digit Recognition | |Title=Lip Biometrics for Digit Recognition | ||
|PublicationType=Conference Paper | |PublicationType=Conference Paper |
Latest revision as of 21:41, 30 September 2016
Title | Lip Biometrics for Digit Recognition |
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Author | Maycel I. Faraj and Josef Bigun |
Year | 2007 |
PublicationType | Conference Paper |
Journal | |
HostPublication | Computer Analysis of Images and Patterns, Proceedings |
Conference | 12th International Conference on Computer Analysis of Images and Patterns, Vienna, AUSTRIA, AUG 27-29, 2007 |
DOI | http://dx.doi.org/10.1007/978-3-540-74272-2_45 |
Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:239344 |
Abstract | This paper presents a speaker-independent audio-visual digit recognition system that utilizes speech and visual lip signals. The extracted visual features are based on line-motion estimation obtained from video sequences with low resolution (128 ×128 pixels) to increase the robustness of audio recognition. The core experiments investigate lip motion biometrics as stand-alone as well as merged modality in speech recognition system. It uses Support Vector Machines, showing favourable experimental results with digit recognition featuring 83% to 100% on the XM2VTS database depending on the amount of available visual information. |