This paper introduces a novel deformable model for face mapping and its application to automatic person identification. While most face recognition techniques directly model the face, our goal is to model the transformation between face images of the same person. As a global face transformation may be too complex to be modeled in its entirety, it is approximated by a set of local transformation...

Estimating probabilistic deformable template models is a new approach in the fields of computer vision and probabilistic atlases in computational anatomy. A first coherent statistical framework modelling the variability as a hidden random variable has been given by Allassonnière, Amit and Trouvé in [1] in simple and mixture of deformable template models. A consistent stochastic algorithm has be...

Pose and illumination changes from picture to picture are two main barriers toward full automatic face recognition. In this paper, a novel method to handle both pose and lighting condition simultaneously is proposed, which calibrates the pose and lighting condition to a pre-set reference condition through an illumination invariant 3D face reconstruction. First, some located facial landmarks and...

We present an algorithm that automatically establishes dense correspondences between a large number of 3D faces. Starting from automatically detected sparse correspondences on the outer boundary of 3D faces, the algorithm triangulates existing correspondences and expands them iteratively by matching points of distinctive surface curvature along the triangle edges. After exhausting keypoint matc...

We describe an approach for extracting facial features from images and for determining the spatial organization between these features using the concept of a deformable template. This is a parameterized geometric model of the object to be recognized together with a measure of how well it fits the image data. Variations in the parameters correspond to allowable deformations of the object and can...

At present, many approaches have been proposed for deformable face alignment with varying degrees of success. However, the common drawback to nearly all these approaches is the inaccurate landmark registrations. The registration errors which occur are predominantly heterogeneous (i.e. low error for some frames in a sequence and higher error for others). In this paper we propose an approach for ...

For scalable and model-based coding of videophone sequence at very low bit rates, a 2-D scalable face model has to be designed. In this paper, an efficient algorithm is presented for the automatic detection of chin contour of a person face. The chin is first represented by a deformable template consisting of two parabolas. Then, a cost function is minimized to find the best fit of template to t...

We present a novel method for the shape and motion estimation of a deformable model using error residuals from model-based motion analysis. The motion of the model is first estimated using a model-based least squares method. Using the residuals from the least squares solution, the non-rigid structure of the model can be better estimated by computing how changes in the shape of the model affect ...