A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Identification by Fitting a 3D Morphable Model Using Linear Shape and Texture Error Functions
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Optimal postures and positioning for human body scanning
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
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
Spacetime faces: high resolution capture for modeling and animation
ACM SIGGRAPH 2004 Papers
Efficient 3D reconstruction for face recognition
Pattern Recognition
Automatic 3D reconstruction for face recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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We propose a method that can reconstruct both a 3D facial shape and camera poses from freehand multi-viewpoint snapshots. This method is based on Active Shape Model (ASM) using a facial shape database. Most ASM methods require an image in which the camera pose is known, but our method does not require this information. First, we choose an initial shape by selecting the model from the database which is most suitable to input images. Then, we improve the model by morphing it to fit the input images. Next, we estimate the camera poses using the morphed model. Finally we repeat the process, improving both the facial shape and the camera poses until the error between the input images and the computed result is minimized. Through experimentation, we show that our method reconstructs the facial shape within 3.5 mm of the ground truth.