A new multidisciplinary project extending over a number of years was initiated in Hungary to combine knowledgebases of different disciplines like anthropology, medical, mechanical, archaeological sciences etc. to computerize the face reconstruction.. A research group (BME Cooperation Research Center for Biomechanics) was formed representing several organizations that are cooperateing during the...

In this paper we propose a novel 3D face recognition system. Furthermore we propose and discuss the development of a 3D reconstruction system designed specifically for the purpose of face recognition. The reconstruction subsystem utilises a capture rig comprising of six cameras to obtain two independent stereo pairs of the subject face during a structured light projection with the remaining two...

Existing single view, 3D face reconstruction methods can produce beautifully detailed 3D results, but typically only for near frontal, unobstructed viewpoints. We describe a system designed to provide detailed 3D reconstructions of faces viewed under extreme conditions, out of plane rotations, and occlusions. Motivated by the concept of bump mapping, we propose a layered approach which decouple...

Based on linear regression, a novel method called reconstructive discriminant analysis (RDA) is developed for feature extraction and dimensionality reduction (DR). RDA is induced from linear Regression classification (LRC). LRC assumes each class lies on a linear subspace and finds the nearest subspace for a given sample. But the original space cannot guarantee that the given sample matches its...

A number of investigators have had success using domain specific prior knowledge to produce improved superresolution images of faces (“hallucinating faces”). These efforts address the scenario where a face image is obtained from a low-resolution camera. A related but less studied problem occurs when the missing information is the result of occlusion rather than low camera resolution, as in the ...

3D face reconstruction from a single 2D image is challenging problem with broad applications. Recent methods typically aim to learn CNN-based model that regresses coefficients of Morphable Model (3DMM) images render or dense alignment. However, the shortage training data annotations considerably limits performance those methods. To alleviate this issue, we propose novel 2D-assisted self-supervi...

Three-dimensional face dense alignment and reconstruction in the wild is a challenging problem as partial facial information commonly missing occluded large pose images. Large head variations also increase solution space make modeling more difficult. Our key idea to model occlusion decompose this task into several relatively manageable subtasks. To end, we propose an end-to-end framework, terme...