Feature extraction from faces using deformable templates
International Journal of Computer Vision
Active vision
A framework for spatiotemporal control in the tracking of visual contours
International Journal of Computer Vision
Lip-motion analysis for speech segmentation in noise
Speech Communication
Learning to track the visual motion of contours
Artificial Intelligence - Special volume on computer vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Deformable Templates for Feature Extraction from Medical Images
ECCV '90 Proceedings of the First European Conference on Computer Vision
Real-Time Lip Tracking for Audio-Visual Speech Recognition Applications
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Visual speech recognition using active shape models and hidden Markov models
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 02
A Probabilistic Dynamic Contour Model for Accurate and Robust Lip Tracking
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Real-Time Tracking Using Trust-Region Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real time contour tracking with a new edge detector
Real-Time Imaging
A local region based approach to lip tracking
Pattern Recognition
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A new method for tracking contours of moving objects in clutter is presented. For a given object, a model of its contours is learned from training data in the form of a subset of contour space. Greater complexity is added to the contour model by analyzing rigid and non-rigid transformations of contours separately. In the course of tracking, multiple contours may be observed due to the presence of extraneous edges in the form of clutter; the learned model guides the algorithm in picking out the correct one. The algorithm, which is posed as a solution to a minimization problem, is made efficient by the use of several iterative schemes. Results applying the proposed algorithm to the tracking of a flexing finger and to a conversing individual's lips are presented.