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» Robust Active Appearance Model Matching
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FGR
2006
IEEE
157views Biometrics» more  FGR 2006»
13 years 10 months ago
Evaluating Error Functions for Robust Active Appearance Models
Active appearance models (AAMs) are generative parametric models commonly used to track faces in video sequences. A limitation of AAMs is they are not robust to occlusion. A recen...
Barry-John Theobald, Iain Matthews, Simon Baker
ISVC
2007
Springer
13 years 11 months ago
Robust Infants Face Tracking Using Active Appearance Models: A Mixed-State CONDENSATION Approach
Abstract. In this paper a new extension of the CONDENSATION algorithm, with application to infants face tracking, will be introduced. In this work we address the problem of trackin...
Luigi Bagnato, Matteo Sorci, Gianluca Antonini, Gi...
ECCV
1998
Springer
14 years 6 months ago
Active Appearance Models
?We describe a new method of matching statistical models of appearance to images. A set of model parameters control modes of shape and gray-level variation learned from a training ...
Timothy F. Cootes, Gareth J. Edwards, Christopher ...
ISVC
2007
Springer
13 years 11 months ago
Real-Time 3D Face Tracking with Mutual Information and Active Contours
Abstract. We present a markerless real-time, model-based 3D face tracking methodology. The system combines two robust and complimentary optimization-based strategies, namely active...
Giorgio Panin, Alois Knoll
BMVC
2002
13 years 7 months ago
Comparing Variations on the Active Appearance Model Algorithm
The Active Appearance Model (AAM) algorithm has proved to be a successful method for matching statistical models of appearance to new images. Since the original algorithm was desc...
Timothy F. Cootes, Panachit Kittipanya-ngam