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ICPR
2002
IEEE
14 years 21 days ago
Tracking Objects Using Recovered Physical Motion Parameters
This paper presents a physical model-based method for recovering and tracking nonrigid motion of elastic objects. The proposed method recovers the motion in terms of actual physic...
Yong Zhang, Dmitry B. Goldgof, Sudeep Sarkar, Leon...
3DOR
2010
13 years 2 months ago
SHREC'10 Track: Non-rigid 3D Shape Retrieval
Non-rigid shape matching is one of the most challenging fields in content-based 3D object retrieval. The aim of the SHREC 2010 - Shape Retrieval Contest of Non-rigid 3D Models is ...
Zhouhui Lian, Afzal Godil, Thomas Fabry, Takahiko ...
CORR
2011
Springer
222views Education» more  CORR 2011»
12 years 11 months ago
Weakly Supervised Learning of Foreground-Background Segmentation using Masked RBMs
Abstract. We propose an extension of the Restricted Boltzmann Machine (RBM) that allows the joint shape and appearance of foreground objects in cluttered images to be modeled indep...
Nicolas Heess, Nicolas Le Roux, John M. Winn
NIPS
2004
13 years 9 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...
CVPR
2008
IEEE
14 years 9 months ago
Motion segmentation via robust subspace separation in the presence of outlying, incomplete, or corrupted trajectories
We examine the problem of segmenting tracked feature point trajectories of multiple moving objects in an image sequence. Using the affine camera model, this motion segmentation pr...
René Vidal, Roberto Tron, Shankar Rao, Yi M...