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Sökning: onr:"swepub:oai:DiVA.org:hh-1980" > Lip-motion biometri...

Lip-motion biometrics for audio-visual identity recognition

Faraj, Maycel Isaac, 1979- (författare)
Högskolan i Halmstad,Halmstad Embedded and Intelligent Systems Research (EIS),Chalmers tekniska högskola,Chalmers University of Technology
Tistarelli, Massimo, Professor (opponent)
University of Sassari, Italien
 (creator_code:org_t)
ISBN 9789173851619
Göteborg : Chalmers university of technology, 2008
Engelska 161 s.
Serie: Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie, 0346-718X ; 2842
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)
Abstract Ämnesord
Stäng  
  • Biometric recognition systems have been established as powerful security tools to prevent unknown users from entering high risk systems and areas. They are increasingly being utilized in surveillance and access management (city centers, banks, etc.) by using individuals' physical or biological characteristics. The present study reports on the use of lip motion as a standalone biometric modality as well as a modality integrated with audio speech for identity and digit recognition. First, we estimate motion vectors from a sequence of lip-movement images. The motion is modelled as the distribution of apparent line velocities in the movement of brightness patterns in an image. Then, we construct compact lip-motion features from the regional statistics of the local velocities. These can be used alone or merged with audio features to recognize individuals or speech (digits). In this work, we utilized two classifiers for identification and verification of identity as well as with digit recognition. Although the study is focused on processing lip movements in a video sequence, significant speech processing is a prerequisite given that the contribution of video analysis to speech analysis is studied in conjunction with recognition of humans and what they say (digits). Such integration is necessary to understand multimodel biometric systems to the benefit of recognition performance and robustness against noise. Extensive experiments utilizing one of the largest available databases, XM2VTS, are presented.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)

Nyckelord

Biometrics
Lip motion
Audio-visual signals
Speech recognition
Speaker recognition
Digit recognition
Image analysis
Bildanalys

Publikations- och innehållstyp

vet (ämneskategori)
dok (ämneskategori)

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