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Multiview 3D face modeling has attracted increasing attention recently andhas become one of the potential avenues in future video systems. We aim to makemore reliable and robust automatic feature extraction and natural 3D featureconstruction from 2D features detected on a pair of frontal and profile viewface images. We propose several heuristic algorithms to minimize possibleerrors introduced by prevalent nonperfect orthogonal condition and noncoherentluminance. In our approach, we first extract the 2D features that are visibleto both cameras in both views. Then, we estimate the coordinates of thefeatures in the hidden profile view based on the visible features extracted inthe two orthogonal views. Finally, based on the coordinates of the extractedfeatures, we deform a 3D generic model to perform the desired 3D clonemodeling. Present study proves the scope of resulted facial models forpractical applications like face recognition and facial animation.

Sequential Clustering based Facial Feature Extraction Method for Automatic Creation of Facial Models from Orthogonal Views