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CVPR
2001
IEEE
14 years 6 months ago
Tracking and Modeling Non-Rigid Objects with Rank Constraints
This paper presents a novel solution for flow-based tracking and 3D reconstruction of deforming objects in monocular image sequences. A non-rigid 3D object undergoing rotation and...
Lorenzo Torresani, Danny B. Yang, Eugene J. Alexan...
NIPS
2004
13 years 6 months ago
Joint Tracking of Pose, Expression, and Texture using Conditionally Gaussian Filters
We present a generative model and stochastic filtering algorithm for simultaneous tracking of 3D position and orientation, non-rigid motion, object texture, and background texture...
Tim K. Marks, John R. Hershey, J. Cooper Roddey, J...
AIPR
2001
IEEE
13 years 8 months ago
Model-Based Face Tracking for Dense Motion Field Estimation
When estimating the dense motion field of a video sequence, if little is known or assumed about the content, a limited constraint approach such as optical flow must be used. Since...
Timothy F. Gee, Russell M. Mersereau
FGR
2008
IEEE
301views Biometrics» more  FGR 2008»
13 years 11 months ago
3D facial geometry recovery via group-wise optical flow
We describe an algorithm for automatically finding correspondences from face video sequences. This method is useful to many applications such as face tracking, face modeling and ...
Hui Fang, Nicholas Costen, David Cristinacce, John...
PAMI
2010
238views more  PAMI 2010»
13 years 3 months ago
Tracking Motion, Deformation, and Texture Using Conditionally Gaussian Processes
—We present a generative model and inference algorithm for 3D nonrigid object tracking. The model, which we call G-flow, enables the joint inference of 3D position, orientation, ...
Tim K. Marks, John R. Hershey, Javier R. Movellan