Coding, Analysis, Interpretation, and Recognition of Facial Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
FG '98 Proceedings of the 3rd. International Conference on Face & Gesture Recognition
Facial Expression Space Learning
PG '02 Proceedings of the 10th Pacific Conference on Computer Graphics and Applications
Cluster-preserving Embedding of Proteins
Cluster-preserving Embedding of Proteins
Nonlinear Mapping of Multi-View Face Patterns to a Gaussian Distribution in a Low Dimensional Space
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
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
Video-based face recognition using probabilistic appearance manifolds
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
On bending invariant signatures for surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 12th annual ACM international conference on Multimedia
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Static topographic modeling for facial expression recognition and analysis
Computer Vision and Image Understanding
A survey of affect recognition methods: audio, visual and spontaneous expressions
Proceedings of the 9th international conference on Multimodal interfaces
Computer Vision and Image Understanding
Probing dynamic human facial action recognition from the other side of the mean
Proceedings of the 5th symposium on Applied perception in graphics and visualization
A Novel Classifier Based on Enhanced Lipschitz Embedding for Speech Emotion Recognition
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
IEICE - Transactions on Information and Systems
Facial expression recognition based on Local Binary Patterns: A comprehensive study
Image and Vision Computing
Modelling human perception of static facial expressions
Image and Vision Computing
Analyzing facial expression by fusing manifolds
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Adapted active appearance models
Journal on Image and Video Processing
Facial expression recognition on multiple manifolds
Pattern Recognition
Implicit image tagging via facial information
Proceedings of the 2nd international workshop on Social signal processing
Learning video manifold for segmenting crowd events and abnormality detection
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
A temporal latent topic model for facial expression recognition
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
DTTM: a discriminative temporal topic model for facial expression recognition
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part I
Automatic facial expression recognition using linear and nonlinear holistic spatial analysis
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Facial expression analysis using nonlinear decomposable generative models
AMFG'05 Proceedings of the Second international conference on Analysis and Modelling of Faces and Gestures
Automatic 3d facial expression analysis in videos
AMFG'05 Proceedings of the Second international conference on Analysis and Modelling of Faces and Gestures
Appearance manifold of facial expression
ICCV'05 Proceedings of the 2005 international conference on Computer Vision in Human-Computer Interaction
Facial expression recognition using spatiotemporal boosted discriminatory classifiers
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
Recognition of 3D facial expression dynamics
Image and Vision Computing
Facial expression recognition using geometric and appearance features
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Computer Vision and Image Understanding
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In this paper, we propose a probabilistic videobased facial expression recognition method on manifolds. The concept of the manifold of facial expression is based on the observation that the images of all possible facial deformations of an individual make a smooth manifold embedded in a high dimensional image space. An enhanced Lipschitz embedding is developed to embed the aligned face appearance in a low dimensional space while keeping the main structure of the manifold. In the embedded space, a complete expression sequence becomes a path on the expression manifold, emanating from a center that corresponds to the neutral expression. Each path consists of several clusters. A probabilistic model of transition between the clusters and paths is learned through training videos in the embedded space. The likelihood of one kind of facial expression is modeled as a mixture density with the clusters as mixture centers. The transition between different expressions is represented as the evolution of the posterior probability of the six basic paths. The experimental results demonstrate that the probabilistic approach can recognize expression transitions effectively. We also synthesize image sequences of changing expressions through the manifold model.