Principal Warps: Thin-Plate Splines and the Decomposition of Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Robust Face Detection Using the Hausdorff Distance
AVBPA '01 Proceedings of the Third International Conference on Audio- and Video-Based Biometric Person Authentication
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection
International Journal of Computer Vision
Fast and Accurate Facial Pose Estimation by Aligning a 3D Appearance Model
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
3D Alignment of Face in a Single Image
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
2D vs. 3D Deformable Face Models: Representational Power, Construction, and Real-Time Fitting
International Journal of Computer Vision
Automatic feature localisation with constrained local models
Pattern Recognition
Real Time Feature Based 3-D Deformable Face Tracking
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Real-time combined 2D+3D active appearance models
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Adding facial actions into 3D model search to analyse behaviour in an unconstrained environment
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Using 3d models for real-time facial feature tracking, pose estimation, and expression monitoring
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
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We present an automatic method for locating facial features and estimating head pose in 2D images and video using a 3D shape model and local view-based texture patches. After automatic initialization, the 3D pose and shape are refined iteratively to optimize the match between the appearance predicted by the model, and the image. The local texture patches are generated using the current 3D pose and shape, and the locations of model points are refined by neighbourhood search, using normalized cross-correlation to provide some robustness to illumination. A key aspect is the presentation of a large-scale quantitative evaluation, comparing the method to a well-established 2D approach. We show that the accuracy of feature location for the 3D system is comparable to that of the 2D system for near-frontal faces, but significantly better for sequences which involve large rotations, obtaining estimates of pose to within 10º at headings of up to 70º.