System identification: theory for the user
System identification: theory for the user
Recognizing Human Facial Expressions From Long Image Sequences Using Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Classification of Single Facial Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning and Classification of Complex Dynamics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Analysis of Facial Expressions: The State of the Art
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Action Units for Facial Expression Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D Real-Time Head Tracking Fusing Color Histograms and Stereovision
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Estimation of Rigid and Non-Rigid Facial Motion Using Anatomical Face Model
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
A Region-Based Method for Model-Free Object Tracking
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Model-Based Face Tracking for View-Independent Facial Expression Recognition
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Separability of Pose and Expression in Facial Tracking and Animation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Mixed-State Condensation Tracker with Automatic Model-Switching
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Face Recognition Based on Fitting a 3D Morphable Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Capturing Subtle Facial Motions in 3D Face Tracking
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Facial expression recognition from video sequences: temporal and static modeling
Computer Vision and Image Understanding - Special issue on Face recognition
Probabilistic recognition of human faces from video
Computer Vision and Image Understanding - Special issue on Face recognition
Real Time Facial Expression Recognition with Adaboost
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Active and Dynamic Information Fusion for Facial Expression Understanding from Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Effective Gaussian Mixture Learning for Video Background Subtraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous Facial Action Tracking and Expression Recognition Using a Particle Filter
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Classifying Facial Gestures in Presence of Head Motion
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Matching 2.5D Face Scans to 3D Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
An active model for facial feature tracking
EURASIP Journal on Applied Signal Processing
Interactive analysis and synthesis of facial expressions based on personal facial expression space
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
Robust online appearance models for visual tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual tracking and recognition using appearance-adaptive models in particle filters
IEEE Transactions on Image Processing
On Appearance Based Face and Facial Action Tracking
IEEE Transactions on Circuits and Systems for Video Technology
Pose-Invariant Facial Expression Recognition Using Variable-Intensity Templates
International Journal of Computer Vision
Proceedings of the 2009 international conference on Multimodal interfaces
Real-time face tracking and pose estimation with partitioned sampling and relevance vector machine
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Spatiotemporal-boosted DCT features for head and face gesture analysis
HBU'10 Proceedings of the First international conference on Human behavior understanding
Robust classification of face and head gestures in video
Image and Vision Computing
Adaptive facial expression recognition using inter-modal top-down context
ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
Hough forest-based facial expression recognition from video sequences
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
Spatiotemporal features for effective facial expression recognition
ECCV'10 Proceedings of the 11th European conference on Trends and Topics in Computer Vision - Volume Part I
Visual Focus of Attention in Non-calibrated Environments using Gaze Estimation
International Journal of Computer Vision
| Hi-index | 0.00 |
The recognition of facial gestures and expressions in image sequences is an important and challenging problem. Most of the existing methods adopt the following paradigm. First, facial actions/features are retrieved from the images, then the facial expression is recognized based on the retrieved temporal parameters. In contrast to this mainstream approach, this paper introduces a new approach allowing the simultaneous retrieval of facial actions and expression using a particle filter adopting multi-class dynamics that are conditioned on the expression. For each frame in the video sequence, our approach is split into two consecutive stages. In the first stage, the 3D head pose is retrieved using a deterministic registration technique based on Online Appearance Models. In the second stage, the facial actions as well as the facial expression are simultaneously retrieved using a stochastic framework based on second-order Markov chains. The proposed fast scheme is either as robust as, or more robust than existing ones in a number of respects. We describe extensive experiments and provide evaluations of performance to show the feasibility and robustness of the proposed approach.