Hands: a pattern theoretic study of biological shapes
Hands: a pattern theoretic study of biological shapes
Feature extraction from faces using deformable templates
International Journal of Computer Vision
Active shape models—their training and application
Computer Vision and Image Understanding
Graphical Templates for Model Registration
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Mixtures of probabilistic principal component analyzers
Neural Computation
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
Finding Deformable Shapes Using Loopy Belief Propagation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Efficient Optimization of a Deformable Template Using Dynamic Programming
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Rotation Invariant Neural Network-Based Face Detection
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern 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
A Bayesian Mixture Model for Multi-View Face Alignment
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
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
Accurate Face Alignment using Shape Constrained Markov Network
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Bayesian tangent shape model: Estimating shape and pose parameters via bayesian inference
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Deformable Model Fitting by Regularized Landmark Mean-Shift
International Journal of Computer Vision
Personalized 3D-aided 2D facial landmark localization
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Proceedings of the 1st ACM International Conference on Multimedia Retrieval
Learning deformable shape manifolds
Pattern Recognition
Joint face alignment: rescue bad alignments with good ones by regularized re-fitting
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Joint face alignment with non-parametric shape models
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Discriminative bayesian active shape models
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Interactive facial feature localization
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
Locality-Constrained active appearance model
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
A review of motion analysis methods for human Nonverbal Communication Computing
Image and Vision Computing
Image and Vision Computing
Salient and non-salient fiducial detection using a probabilistic graphical model
Pattern Recognition
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In this paper, we present a robust face alignment system that is capable of dealing with exaggerating expressions, large occlusions, and a wide variety of image noises. The robustness comes from our shape regularization model, which incorporates constrained nonlinear shape prior, geometric transformation, and likelihood of multiple candidate landmarks in a three-layered generative model. The inference algorithm iteratively examines the best candidate positions and updates face shape and pose. This model can effectively recover sufficient shape details from very noisy observations. We demonstrate the performance of this approach on two public domain databases and a large collection of real-world face photographs.