Proceedings of the 27th annual conference on Computer graphics and interactive techniques
Learning variable-length Markov models of behavior
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Learning Dynamics of Complex Motions from Image Sequences
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Learning Intrinsic Video Content Using Levenshtein Distance in Graph Partitioning
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Learning and Recognizing Human Dynamics in Video Sequences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Normalized Cuts and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
The Acquisition and Use of Interaction Behavior Models
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Real-time 3-D human body tracking using learnt models of behaviour
Computer Vision and Image Understanding
Motion Primitives and Probabilistic Edit Distance for Action Recognition
Gesture-Based Human-Computer Interaction and Simulation
Finding motion primitives in human body gestures
GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation
Action recognition using motion primitives and probabilistic edit distance
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Human motion synthesis by motion manifold learning and motion primitive segmentation
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
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We wish to model the way in which faces move in video sequences. We represent facial behaviour as a sequence of short actions. Each action is a sample from a statistical model representing the variability in the way it is performed. The ordering of actions is defined using a variable length Markov model. Action models and variable length Markov model are trained from a long (20000 frames) video sequence of a talking face. We propose a novel method of quantitatively evaluating the quality of the synthesis by measuring overlaps of parameter histograms. We apply this method to compare our technique with an alternative model that uses an autoregressive process.