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Fusion of audio and video information for multi modal person authentication
Type of publication: Journal paper
Citation: duc-prl97
Journal: Pattern Recognition Letters
Volume: 18
Number: 9
Year: 1997
Abstract: We present an algorithm functioning as a supervisor module in a multi-expert decision making machine. It uses the Bayes theory in order to estimate the biases of individual expert opinions. The biases are used to calibrate and conciliate expert opinions to a single decision. This supervision technique is applied to the real case of a person authentication technique using two modalities, face and speech. The visual part involves the matching of a coarse grid containing Gabor phase information from face images. The acoustic part is performed by a text-dependent speaker verification system based on Hidden Markov Models. Experimental results show that the proposed fusion method improves the quality of individual expert decisions by reaching success rates of 99.5 \%
Userfields: ipdmembership={vision},
Keywords:
Projects Idiap
Authors Duc, Benoît
Bigün, Elizabeth Saers
Bigün, Josef
Maître, Gilbert
Fischer, Stefan
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