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. © Springer-Verlag Berlin Heidelberg 2007.
Cite
CITATION STYLE
Faraj, M. I., & Bigun, J. (2007). Lip biometrics for digit recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4673 LNCS, pp. 360–365). Springer Verlag. https://doi.org/10.1007/978-3-540-74272-2_45
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