Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstruction of Partially Damaged Face Images Based on a Morphable Face Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Identification across Different Poses and Illuminations with a 3D Morphable Model
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Recognition and Structure from one 2D Model View: Observations on Prototypes, Object Classes and Symmetries
Journal of Cognitive Neuroscience
A Separable Median Filter for Image Noise Smoothing
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Image Processing
Resolution enhancement of monochrome and color video using motion compensation
IEEE Transactions on Image Processing
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This paper presents our method for reconstructing facial image from a partially occluded facial image or a low-resolution one using example-based learning Faces are modeled by linear combinations of prototypes of shape and texture With the shape and texture information from an input facial image, we can estimate optimal coefficients for linear combinations of prototypes of shape and texture by simple projection for least square minimization The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by reconstructing facial image from a partially occluded facial image or a low-resolution one.