NON-LINEAR ACTIVE MODEL FOR MOUTH INNER AND OUTER CONTOURS DETECTION (WedPmPO4)

Author(s) : Pierre Gacon (LIS INPG, France) Pierre-Yves Coulon (LIS INPG, France) Gérard Bailly (ICP INPG, France)

Abstract : Mouth segmentation is an important issue which applies in many multimedia applications as speech reading, face synthesis, recognition or audiovisual communication. Our goal is to have a robust and efficient detection of lips contour. In this paper, we focus on the detection of the inner mouth contour which is a difficult task due to the non-linear appearance variations. We propose a method based on a statistical model of shape with local appearance gaussian descriptors. Our hypothesis is that the response of the local descriptors can be predicted from the shape. This prediction is achieved by a non-linear neural network. We tested this hypothesis with a single speaker task and compared the results with previous methods. Then this approach is generalized to take care of the intra person appearance variability in a multi-speaker task.

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