Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Active shape models—their training and application
Computer Vision and Image Understanding
Active tracking of foveated feature clusters using affine structure
International Journal of Computer Vision
Shape Ambiguities in Structure From Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Synthesizing realistic facial expressions from photographs
Proceedings of the 25th annual conference on Computer graphics and interactive techniques
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Modeling and Animating Realistic Faces from Images
International Journal of Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
3-D Face Modeling Using Two Views and a Generic Face Model with Application to 3-D Face Recognition
AVSS '03 Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face reconstruction from monocular video using uncertainty analysis and a generic model
Computer Vision and Image Understanding - Special issue on Face recognition
Robust and Rapid Generation of Animated Faces from Video Images: A Model-Based Modeling Approach
International Journal of Computer Vision - Special Issue on Research at Microsoft Corporation
Damped Newton Algorithms for Matrix Factorization with Missing Data
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
3D Face Reconstruction from Stereo Video
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Estimating 3D shape from degenerate sequences with missing data
Computer Vision and Image Understanding
Instant Casting Movie Theater: The Future Cast System
IEICE - Transactions on Information and Systems
Face recognition across pose: A review
Pattern Recognition
A comparative study of facial appearance modeling methods for active appearance models
Pattern Recognition Letters
Generic vs. person specific active appearance models
Image and Vision Computing
Efficient 3D reconstruction for face recognition
Pattern Recognition
Age-Invariant Face Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning a generic 3D face model from 2D image databases using incremental Structure-from-Motion
Image and Vision Computing
Model-assisted 3D face reconstruction from video
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
3D model-based face recognition in video
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
An ellipsoidal model for generating realistic 3D facial textures
International Journal of Computer Applications in Technology
A new framework for 3D face reconstruction for self-occluded images
International Journal of Computational Vision and Robotics
Hi-index | 0.01 |
This paper presents a 3D face reconstruction method using multiple 2D face images. Structure from motion (SfM) methods, which have been widely used to reconstruct 3D faces, are vulnerable to point correspondence errors caused by self-occlusion. In order to solve this problem, we propose a shape conversion matrix (SCM) which estimates the ground-truth 2D facial feature points (FFPs) from the observed 2D FFPs corrupted by self-occlusion errors. To make the SCM, the training observed 2D FFPs and ground-truth 2D FFPs are collected by using 3D face scans. An observed shape model and a ground-truth shape model are then built to represent the observed 2D FFPs and the ground-truth 2D FFPs, respectively. Finally, the observed shape model parameter is converted to the ground truth shape model parameter via the SCM. By using the SCM, the true locations of the self-occluded FFPs are estimated exactly with simple matrix multiplications. As a result, SfM-based 3D face reconstruction methods combined with the proposed SCM become more robust against point correspondence errors caused by self-occlusion, and the computational cost is significantly reduced. In experiments, the reconstructed 3D facial shape is quantitatively compared with the 3D facial shape obtained from a 3D scanner, and the results show that SfM-based 3D face reconstruction methods with the proposed SCM show a higher accuracy and a faster processing time than SfM-based 3D face reconstruction methods without the SCM.