Efficient, Robust and Accurate Fitting of a 3D Morphable Model
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Active Appearance Models Revisited
International Journal of Computer Vision
Effective Gaussian Mixture Learning for Video Background Subtraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Object Tracking Via Online Dynamic Spatial Bias Appearance Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual tracking and recognition using appearance-adaptive models in particle filters
IEEE Transactions on Image Processing
On Appearance Based Face and Facial Action Tracking
IEEE Transactions on Circuits and Systems for Video Technology
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Target modeling and model fitting are the two important parts of the problem of object tracking. The former has to provide a good reference for the latter. Online appearance models (OAM) has been successfully used for facial features tracking on account of their strong ability to adapt to variations, however, it suffers from time-consuming model fitting. Inverse Compositional Image Alignment (ICIA) algorithm has been proved to be an efficient, robust and accurate fitting algorithm. In this work, we introduce an efficient online appearance models based on ICIA, and apply it to track head pose and facial actions in video. The performance of the proposed method is evaluated by its real time implementation, and experimental results demonstrate that the algorithm is robust and efficient.