Voxel-based 3D face reconstruction and its application to face recognition using sequential deep learning

2020 ◽  
Vol 79 (25-26) ◽  
pp. 17303-17330 ◽  
Author(s):  
Sahil Sharma ◽  
Vijay Kumar
Keyword(s):  
Deep Learning ◽  
Face Recognition ◽  
3D Face Reconstruction ◽  
3D Face ◽  
Face Reconstruction

3D Face Reconstruction from Two Orthogonal Images for Face Recognition Applications

2012 ◽  
pp. 223-239
Author(s):  
Stefano Berretti ◽  
Alberto Del Bimbo ◽  
Pietro Pala
Keyword(s):  
Face Recognition ◽  
Control Points ◽  
3D Face Reconstruction ◽  
3D Face ◽  
Face Reconstruction ◽  
Face Images ◽  
Model Control ◽  
3D Geometry ◽  
The Face ◽  
Manual Assistance

In this paper, an original hybrid 2D-3D face recognition approach is proposed using two orthogonal face images, frontal and side views of the face, to reconstruct the complete 3D geometry of the face. This is obtained using a model based solution, in which a 3D template face model is morphed according to the correspondence of a limited set of control points identified on the frontal and side images in addition to the model. Control points identification is driven by an Active Shape Model applied to the frontal image, whereas subsequent manual assistance is required for control points localization on the side view. The reconstructed 3D model is finally matched, using the iso-geodesic regions approach against a gallery of 3D face scans for the purpose of face recognition. Preliminary experimental results are provided on a small database showing the viability of the approach.

3D Face Reconstruction from Two Orthogonal Images for Face Recognition Applications

2010 ◽  
Vol 1 (3) ◽  
pp. 42-58 ◽  
Author(s):  
Stefano Berretti ◽  
Alberto Del Bimbo ◽  
Pietro Pala
Keyword(s):  
Face Recognition ◽  
3D Face Reconstruction ◽  
3D Face ◽  
Face Reconstruction

2D face fitting-assisted 3D face reconstruction for pose-robust face recognition

2009 ◽  
Vol 15 (3) ◽  
pp. 417-428 ◽  
Author(s):  
Liting Wang ◽  
Liu Ding ◽  
Xiaoqing Ding ◽  
Chi Fang
Keyword(s):  
Face Recognition ◽  
3D Face Reconstruction ◽  
3D Face ◽  
Face Reconstruction ◽  
Robust Face Recognition

Multi-pose 3D facial texture refinement for face recognition

2018 ◽  
Vol 16 (02) ◽  
pp. 1840006
Author(s):  
Wanshun Gao ◽  
Xi Zhao ◽  
Jun An ◽  
Jianhua Zou
Keyword(s):  
Face Recognition ◽  
State Of The Art ◽  
Competitive Performance ◽  
3D Face Reconstruction ◽  
3D Face ◽  
Face Reconstruction ◽  
Novel Approach ◽  
Art Methods ◽  
The Face ◽  
Facial Images

In this paper, we propose a novel approach for 3D face reconstruction from multi-facial images. Given original pose-variant images, coarse 3D face templates are initialized to reconstruct a refined 3D face mesh in an iteration manner. Then, we warp original facial images to the 2D meshes projected from 3D using Sparse Mesh Affine Warp (SMAW). Finally, we weight the face patches in each view respectively and map the patch with higher weight to a canonical UV space. For facial images with arbitrary pose, their invisible regions are filled with the corresponding UV patches. Poisson editing is applied to blend different patches seamlessly. We evaluate the proposed method on LFW dataset in terms of texture refinement and face recognition. The results demonstrate competitive performance compared to state-of-the-art methods.

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