3D Expressive face model-based tracking algorithm
SPPRA'06 Proceedings of the 24th IASTED international conference on Signal processing, pattern recognition, and applications
Model-Based Tracking by Classification in a Tiny Discrete Pose Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-View AAM Fitting and Construction
International Journal of Computer Vision
Multi-View AAM Fitting and Construction
International Journal of Computer Vision
Evaluation of an appearance-based 3D face tracker using dense 3D data
Machine Vision and Applications
Robust 3D Face Tracking on Unknown Users with Dynamical Active Models
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Efficient illumination independent appearance-based face tracking
Image and Vision Computing
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AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
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
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Hybrid associative retrieval of three-dimensional models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
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PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part I
Pose robust face tracking by combining view-based AAMs and temporal filters
Computer Vision and Image Understanding
Facial Feature Tracking via Evolutionary Multiobjective Optimization
International Journal of Applied Evolutionary Computation
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This paper addresses the three-dimensional (3D) tracking of pose and animation of the human face in monocular image sequences using active appearance models. The major problem of the classical appearance-based adaptation is the high computational time resulting from the inclusion of a synthesis step in the iterative optimization. Whenever the dimension of the face space is large, a real-time performance cannot be achieved. In this paper, we aim at designing a fast and stable active appearance model search for 3D face tracking. The main contribution is a search algorithm whose CPU-time is not dependent on the dimension of the face space. Using this algorithm, we show that both the CPU-time and the likelihood of a nonaccurate tracking are reduced. Experiments evaluating the effectiveness of the proposed algorithm are reported, as well as method comparison and tracking synthetic and real image sequences.