Three-Dimensional Head Tracking and Facial Expression Recovery Using an Anthropometric Muscle-Based Active Appearance Model

This paper describes a novel 3-D model-based tracking algorithm allowing the real-time recovery of 3-D position, orientation, and facial expressions of a moving head. The method uses a 3-D anthropometric muscle-based active appearance model (3-D AMB AAM), a feature-based matching algorithm, and an e...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2008-08, Vol.57 (8), p.1578-1588
Main Authors: Cordea, M.D., Petriu, E.M., Petriu, D.C.
Format: Article
Language:English
Subjects:
3-D head
Active appearance model
Active appearance model (AAM)
Actuators
Algorithms
anthropometric
Control equipment
face analysis
Face detection
face tracking
Facial
Head
human-computer interaction (HCI)
Image motion analysis
Instrumentation
Mathematical models
model-based video coding (MBVC)
muscle based
Muscles
Optical filters
Recovery
Shape
Tracking
Video coding
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Description
Summary:This paper describes a novel 3-D model-based tracking algorithm allowing the real-time recovery of 3-D position, orientation, and facial expressions of a moving head. The method uses a 3-D anthropometric muscle-based active appearance model (3-D AMB AAM), a feature-based matching algorithm, and an extended Kalman filter (EKF) pose and expression estimator. Our model is an extension of the classical 2-D AAM and uses a generic 3-D wireframe model of the face based on two sets of controls: the anatomically motivated muscle actuators to model facial expressions and the statistically based anthropometrical controls to model different facial types.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2008.923784