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
Automatic Analysis of Facial Expressions: The State of the Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Recognizing Facial Expression: Machine Learning and Application to Spontaneous Behavior
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A 3D Facial Expression Database For Facial Behavior Research
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
3D Facial Expression Recognition Based on Primitive Surface Feature Distribution
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Human computing and machine understanding of human behavior: a survey
Proceedings of the 8th international conference on Multimodal interfaces
Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Face Recognition via Sparse Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel approach to classification of facial expressions from 3D-mesh datasets using modified PCA
Pattern Recognition Letters
A survey of approaches and challenges in 3D and multi-modal 3D+2D face recognition
Computer Vision and Image Understanding
3-D face detection, landmark localization, and registration using a point distribution model
IEEE Transactions on Multimedia
A Unified Probabilistic Framework for Spontaneous Facial Action Modeling and Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Manifold based analysis of facial expression
Image and Vision Computing
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Partial Face Biometry Using Shape Decomposition on 2D Conformal Maps of Faces
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
A Dynamic Texture-Based Approach to Recognition of Facial Actions and Their Temporal Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bilinear Models for 3-D Face and Facial Expression Recognition
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Representation Plurality and Fusion for 3-D Face Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Local Binary Patterns and Its Application to Facial Image Analysis: A Survey
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Regression-based intensity estimation of facial action units
Image and Vision Computing
Multi-scale local binary pattern histograms for face recognition
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
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Textured 3D face models capture precise facial surfaces along with the associated textures, making it possible for an accurate description of facial activities. In this paper, we present a unified probabilistic framework based on a novel Bayesian Belief Network (BBN) for 3D facial expression and Action Unit (AU) recognition. The proposed BBN performs Bayesian inference based on Statistical Feature Models (SFM) and Gibbs-Boltzmann distribution and feature a hybrid approach in fusing both geometric and appearance features along with morphological ones. When combined with our previously developed morphable partial face model (SFAM), the proposed BBN has the capacity of conducting fully automatic facial expression analysis. We conducted extensive experiments on the two public databases, namely the BU-3DFE dataset and the Bosphorus dataset. When using manually labeled landmarks, the proposed framework achieved an average recognition rate of 94.2% and 85.6% for the 7 and 16AU on face data from the Bosphorus dataset respectively, and 89.2% for the six universal expressions on the BU-3DFE dataset. Using the landmarks automatically located by SFAM, the proposed BBN still achieved an average recognition rate of 84.9% for the six prototypical facial expressions. These experimental results demonstrate the effectiveness of the proposed approach and its robustness in landmark localization errors.