An Analytic-to-Holistic Approach for Face Recognition Based on a Single Frontal View
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
View-Based Active Appearance Models
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Minimum Variance Estimation of 3D Face Shape from Multi-view
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Automatic 3D reconstruction for face recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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This paper proposes a novel face texture mapping framework for 3D face reconstruction from a single frontal view or half-profile view facial image. Face reconstruction method that originates from the proposed framework, unlike most of the existing ones, is novel in the sense that it is not tightly coupled to a specific face model, and yet it simplifies the pose estimation problem which is pivotal to the success of face reconstruction. This paper details the proposed framework, and illustrates how it addresses the ill-posed pose estimation problem, of which the solution is optimal in the least square sense. With accurate pose estimation of face, precise texture mapping is thus made possible to allow photo realistic rendering of face images in the 3D space. Experimental results demonstrates that reliable and photo realistic 3D face reconstruction can be easily realized in our framework by utilizing a generic 3D face model, standard Haar-like feature based detector and active appearance model. With proposed frame work, face recognition systems could be more robust to pose changes by reconstructing frontal faces from non-frontal ones.