Rigid and non-rigid face motion tracking by aligning texture maps and stereo 3D models
Pattern Recognition Letters
Inferring facial expressions from videos: Tool and application
Image Communication
Simultaneous Facial Action Tracking and Expression Recognition in the Presence of Head Motion
International Journal of Computer Vision
Dynamic vs. Static Recognition of Facial Expressions
AmI '08 Proceedings of the European Conference on Ambient Intelligence
Three-dimensional face pose detection and tracking using monocular videos: tool and application
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on cybernetics and cognitive informatics
Natural Facial Expression Recognition Using Dynamic and Static Schemes
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Structure and appearance features for robust 3D facial actions tracking
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
SPPRA '08 Proceedings of the Fifth IASTED International Conference on Signal Processing, Pattern Recognition and Applications
Efficient facial expression recognition for human robot interaction
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Person-independent monocular tracking of face and facial actions with multilinear models
AMFG'07 Proceedings of the 3rd international conference on Analysis and modeling of faces and gestures
Effecient online appearance models for object tracking
MUSP'10 Proceedings of the 10th WSEAS international conference on Multimedia systems & signal processing
A head pose and facial actions tracking method based on effecient online appearance models
WSEAS Transactions on Information Science and Applications
Improving dynamic facial expression recognition with feature subset selection
Pattern Recognition Letters
Real-time facial animation from live video tracking
SCA '11 Proceedings of the 2011 ACM SIGGRAPH/Eurographics Symposium on Computer Animation
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
3D face tracking using appearance registration and robust iterative closest point algorithm
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Rigid and non-rigid face motion tracking by aligning texture maps and stereo-based 3d models
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Combined head, lips, eyebrows, and eyelids tracking using adaptive appearance models
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
A compact association of particle filtering and kernel based object tracking
Pattern Recognition
A compound eigenspace for recognizing directed human activities
ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part II
Facial expression recognition using tracked facial actions: Classifier performance analysis
Engineering Applications of Artificial Intelligence
Pose-invariant face recognition in videos for human-machine interaction
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2
Connecting users to virtual worlds within MPEG-V standardization
Image Communication
Parameterless Local Discriminant Embedding
Neural Processing Letters
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In this work, we address the problem of tracking faces and facial actions in a single video sequence. The main contributions of the paper are as follows. First, we develop a particle filter based framework for tracking the global 3-D motion of a face using a statistical facial appearance model. Second, we propose a framework for tracking the 3-D face pose as well as the local motion of inner features of the face due for instance to spontaneous facial actions, using an adaptive appearance model. We allow the statistics of the facial appearance as well as the dynamics to be adaptively updated during tracking. Third, we propose a variant of the second framework based on a heuristic search. Tracking real video sequences demonstrated the effectiveness of the developed methods. Accurate tracking was obtained even in the presence of perturbing factors including significant head pose and facial expression variations, occlusions, and illumination changes