scholarly journals 3D Face Reconstruction Techniques: Passive Methods

2019 ◽  
Vol 8 (2) ◽  
pp. 4354-4364
Keyword(s):  
3D Face Reconstruction ◽  
3D Images ◽  
3D Face ◽  
Image Reproduction ◽  
Face Reconstruction ◽  
The Face ◽  
History Of ◽  
Human Pose ◽  
Improved Accuracy ◽  
Pose Identification

In the recent literature, 3D face reconstruction received wide interest and has become one of the significant areas of research. 3D face reconstruction provides in depth details on geometrics, texture and color of the face, which are utilized in different applications. It supports a multitude of applications, ranging from face recognition and surveillance to medical imaging, gaming, animation, and virtual reality. This paper attempts to consolidate the research works that have happened in the history of 3D face reconstruction. Also, we try to classify the existing methods based on the input for the process. The databases used in the recent works are discussed and the performance evaluation of methods on different databases is analyzed. The challenges addressed in recent studies are mainly focused on the faster reconstruction of 3D Images, improved accuracy of reconstructed images, human pose identification, image reproduction with higher resolution. Researchers have also tried to address occlusion related problems. Passive methods, used by different researchers are analyzed and their effects on different parameters are discussed in this work. Finally, possible future areas for improvement in terms of reconstructions are presented for the benefit of researchers.

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.

scholarly journals Fast Modelling Algorithm for Realistic Three-Dimensional Human Face for Film and Television Animation

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Limin Xu
Keyword(s):  
Three Dimensional ◽  
Reconstruction Method ◽  
Feature Points ◽  
Human Face ◽  
3D Face Reconstruction ◽  
3D Face ◽  
Film And Television ◽  
Face Reconstruction ◽  
Reconstruction Performance ◽  
The Face

Aiming at the face photos of film and television animation, this paper proposes a new fast three-dimensional (3D) face modelling algorithm. First of all, based on the LBF algorithm, this paper proposes a multifeature selection idea to automatically detect multiple features of the face. Secondly, in order to solve the shortcomings of slow training speed while achieving large pose face alignment, the regression-based CNN is selected as the algorithm to achieve fast convergence. Then, due to the influence of various factors, the extracted feature points are not completely correct, and Gabor features are used to screen the matching of feature points. Finally, by analysing the principle of 3DMM 3D face reconstruction, a single-view 3D face reconstruction method based on CNN is proposed. The experimental results show that the algorithm in this paper has good reconstruction performance and real-time performance and can realize the rapid modelling of human face.

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.

Coarse-to-fine multiview 3d face reconstruction using multiple geometrical features

2017 ◽  
Vol 77 (1) ◽  
pp. 939-966 ◽  
Author(s):  
Peng Dai ◽  
Xue Wang ◽  
Weihang Zhang
Keyword(s):  
3D Face Reconstruction ◽  
3D Face ◽  
Face Reconstruction ◽  
Geometrical Features ◽  
Coarse To Fine

Multi-objective Evolutionary 3D Face Reconstruction Based on Improved Encoder-Decoder Network

2021 ◽  
Author(s):  
Xingjuan Cai ◽  
Yihao Cao ◽  
Yeqing Ren ◽  
Zhihua Cui ◽  
Wensheng Zhang
Keyword(s):  
3D Face Reconstruction ◽  
3D Face ◽  
Multi Objective ◽  
Face Reconstruction

State of the Art on Monocular 3D Face Reconstruction, Tracking, and Applications

2018 ◽  
Vol 37 (2) ◽  
pp. 523-550 ◽  
Author(s):  
M. Zollhöfer ◽  
J. Thies ◽  
P. Garrido ◽  
D. Bradley ◽  
T. Beeler ◽  
...  
Keyword(s):  
State Of The Art ◽  
3D Face Reconstruction ◽  
3D Face ◽  
Face Reconstruction

scholarly journals Joint Face Alignment and 3D Face Reconstruction with Application to Face Recognition

2020 ◽  
Vol 42 (3) ◽  
pp. 664-678 ◽  
Author(s):  
Feng Liu ◽  
Qijun Zhao ◽  
Xiaoming Liu ◽  
Dan Zeng
Keyword(s):  
Face Recognition ◽  
Face Alignment ◽  
3D Face Reconstruction ◽  
3D Face ◽  
Face Reconstruction

Example-based 3D face reconstruction from uncalibrated frontal and profile images

2015 ◽  
Author(s):  
Jing Li ◽  
Shuqin Long ◽  
Dan Zeng ◽  
Qijun Zhao
Keyword(s):  
3D Face Reconstruction ◽  
3D Face ◽  
Face Reconstruction
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