Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Tracking Using Adaptive Color Mixture Models
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume I - Volume I
Incremental PCA or On-Line Visual Learning and Recognition
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Illumination ratio image: synthesizing and recognition with varying illuminations
Pattern Recognition Letters
Illumination Normalization for Robust Face Recognition Against Varying Lighting Conditions
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Illumination Modeling and Normalization for Face Recognition
AMFG '03 Proceedings of the IEEE International Workshop on Analysis and Modeling of Faces and Gestures
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Active Appearance Models Revisited
International Journal of Computer Vision
Constructing and Fitting Active Appearance Models With Occlusion
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 5 - Volume 05
Real-time combined 2D+3D active appearance models
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Robust online appearance models for visual tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual tracking and recognition using appearance-adaptive models in particle filters
IEEE Transactions on Image Processing
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Pose robust face tracking by combining view-based AAMs and temporal filters
Computer Vision and Image Understanding
Hierarchical On-line Appearance-Based Tracking for 3D head pose, eyebrows, lips, eyelids and irises
Image and Vision Computing
Information Sciences: an International Journal
Pattern Recognition Letters
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The active appearance model (AAM) is a well-known model that can represent a non-rigid object like the face effectively. However, the AAM often fails to converge correctly when the illumination conditions of face images change largely because it uses a set of fixed appearance basis vectors that are usually obtained in a training phase. To overcome this problem, we propose an adaptive AAM that updates the appearance basis vectors with the current face image by the incremental principal component analysis (PCA). However, the update of the appearance basis vectors with ill-fitted face images can worsen the AAM fitting to the forthcoming face images. To avoid this situation, we devise a conditional update method that updates the appearance basis vectors when the AAM fitting is good and the AAM reconstruction error is large. We evaluate the goodness of AAM fitting in terms of the number of outliers. When the AAM fitting is good we update the online appearance model (OAM) parameters, where the OAM is taken to keep the variation of input face image continuously, and also evaluate the goodness of the appearance basis vectors in terms of the magnitude of AAM reconstruction error. When the appearance basis vectors of the current AAM produces a large AAM reconstruction error, we update the appearance basis vectors using the incremental PCA. The proposed conditional update of the appearance basis vectors stabilizes the AAM fitting and improves the face tracking performance especially when the illumination condition changes very dynamically. Experimental results show that the adaptive AAM is superior to the conventional AAM in terms of the occurrence rate of fitting error and the fitting accuracy.