IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Vision and Applications - Special issue: IEEE WACV
Head Tracking via Robust Registration in Texture Map Images
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Framework for Model-Based Tracking Experiments in Image Sequences
International Journal of Computer Vision
Pose Robust Face Tracking by Combining Active Appearance Models and Cylinder Head Models
International Journal of Computer Vision
“Dive into the Movie” Audience-Driven Immersive Experience in the Story
IEICE - Transactions on Information and Systems
Realtime performance-based facial animation
ACM SIGGRAPH 2011 papers
An investigation of model bias in 3d face tracking
AMFG'05 Proceedings of the Second international conference on Analysis and Modelling of Faces and Gestures
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We present a formal methodology for the integration of optical flow and deformable models. The optical flow constraint equation provides a non-holonomic constraint on the motion of the deformable model. In this augmented system, forces computed from edges and optical flow are used simultaneously. When this dynamic system is solved, a model-based least-squares solution for the optical flow is obtained and improved estimation results are achieved. The use of a 3-D model reduces or eliminates problems associated with optical flow computation. This approach instantiates a general methodology for treating visual cues as constraints on deformable models. We apply this framework to human face shape and motion estimation. Our 3-D deformable face model uses a small number of parameters to describe a rich variety of face shapes and facial expressions. We present experiments in extracting the shape and motion of a face from image sequences.