Restoration of Partially Occluded Shapes of Faces Using Neural Networks

Abstract

One of the major difficulties encountered in the development of face image processing algorithms, is the possible presence of occlusions that hide part of the face images to be processed. Typical examples of facial occlusions include sunglasses, beards, hats and scarves. In our work we address the problem of restoring the overall shape of faces given only the shape presentation of a small part of the face. For this purpose a novel technique which utilizes combination of Hopfield and Multi-Layer Perceptron (MLP) neural networks was used. According to the experimental results it is possible to recover with reasonable accuracy the overall shape of faces even in the case where a substantial part of the shape of a given face is not visible. The presented technique could form the basis for developing face image processing systems capable of dealing with occluded faces.