Mouth region localization method based on gaussian mixture model

Authors:
Kenichi Kumatani;Rainer Stiefelhagen
Affiliations:
Interactive Systems Labs, Universitaet Karlsruhe (TH), Karlsruhe, Germany;Interactive Systems Labs, Universitaet Karlsruhe (TH), Karlsruhe, Germany
Venue:
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
Year:
2006

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Abstract

This paper presents a new mouth region localization method which uses the Gaussian mixture model (GMM) of feature vectors extracted from mouth region images. The discrete cosine transformation (DCT) and principle component analysis (PCA) based feature vectors are evaluated in mouth localization experiments. The new method is suitable for audio-visual speech recognition. This paper also introduces a new database which is available for audio visual processing. The experimental results show that the proposed system has high accuracy for mouth region localization (more than 95 %) even if the tracking results of preceding frames are unavailable.