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» Reversing Motion Vector Fields
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AIPR
2001
IEEE
14 years 1 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
PAMI
2006
126views more  PAMI 2006»
13 years 9 months ago
A 3D Shape Constraint on Video
We propose to combine the information from multiple motion fields by enforcing a constraint on the surface normals (3D shape) of the scene in view. The fact that the shape vectors ...
Hui Ji, Cornelia Fermüller
CVPR
2003
IEEE
14 years 11 months ago
Video Segmentation Based on Graphical Models
This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field...
Kia-Fock Loe, Tele Tan, Yang Wang 0002
CEE
2010
119views more  CEE 2010»
13 years 10 months ago
Block-matching-based motion field generation utilizing directional edge displacement
A motion field generation algorithm using block matching of edge-flag histograms has been developed aiming at its application to motion recognition systems. Use of edge flags inste...
Hitoshi Hayakawa, Tadashi Shibata
VMV
2008
117views Visualization» more  VMV 2008»
13 years 11 months ago
High-speed Motion Analysis with Multi-Exposure Images
We propose a method to estimate dense motion vector fields from multi-exposure images. Our approach relies on finding a sparse set of correspondences between features in a single-...
Christian Linz, Timo Stich, Marcus A. Magnor