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
Computer generated animation of faces
ACM '72 Proceedings of the ACM annual conference - Volume 1
Head Pose Determination from One Image Using a Generic Model
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
3D Head Pose Estimation without Feature Tracking
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
3D head pose computation from 2D images: templates versus features
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol.2)-Volume 2 - Volume 2
Model-Based Head Pose Tracking With Stereovision
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Combining PCA and LFA for Surface Reconstruction from a Sparse Set of Control Points
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
A dynamic component deforming model for face shape reconstruction
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
Accurate face models from uncalibrated and Ill-Lit video sequences
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
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Human beings are born with a natural capacity of recovering shape from merely one image. However, it is still a challenging mission for current techniques to make a computer have such an ability. To simulate the modeling procedure of human visual system, a Ternary Deformation Framework (TDF) is proposed to reconstruct a realistic 3D face from one 2D frontal facial image, with prior knowledge regarding facial shape learnt from a 3D face data set. Based upon the reconstructed 3D face, a novelmethod via linear regression is then proposed to estimate that person's pose on another image with pose variations. Simulation results show that TDF outperforms the conventional methods with respect to the modeling precision and that reconstructions on real photographs have achieved favorable visual effects. Moreover, the comparison results validated the effectiveness of using the 3D face in the proposed pose estimation method.