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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
IPMI
2005
Springer
13 years 10 months ago
Robust Active Appearance Model Matching
A novel robust active appearance model (AAM) matching algorithm is presented. The method consists of two main stages. First, initial residuals are clustered by a non parametric mea...
Reinhard Beichel, Horst Bischof, Franz Leberl, Mil...
ICVS
2009
Springer
13 years 11 months ago
Increasing the Robustness of 2D Active Appearance Models for Real-World Applications
Abstract. This paper presents an approach to increase the robustness of Active Appearance Models (AAMs) within the scope of humanrobotinteraction. Due to unknown environments with ...
Ronny Stricker, Christian Martin, Horst-Michael Gr...
ICIP
2009
IEEE
14 years 5 months ago
Tongue Tracking In Ultrasound Images With Active Appearance Models
Tongue Ultrasound imaging is widely used for human speech production analysis and modeling. In this paper, we propose a novel method to automatically detect and track the tongue c...
ECCV
2006
Springer
14 years 6 months ago
Resolution-Aware Fitting of Active Appearance Models to Low Resolution Images
Abstract. Active Appearance Models (AAM) are compact representations of the shape and appearance of objects. Fitting AAMs to images is a difficult, non-linear optimization task. Tr...
Göksel Dedeoglu, Simon Baker, Takeo Kanade