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» Learning for Optical Flow Using Stochastic Optimization
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PAMI
2010
238views more  PAMI 2010»
13 years 6 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
MVA
1996
129views Computer Vision» more  MVA 1996»
13 years 9 months ago
Computation of Optical Flow Using Dynamic Programming
This paper presents an original algorithm for the computation of optical ow called Orthogonal Dynamic Programming (ODP) as well as several enhancements to it. The principle is to ...
Georges Quénot
IJCV
2012
11 years 10 months ago
Sparse Occlusion Detection with Optical Flow
Abstract We tackle the problem of detecting occluded regions in a video stream. Under assumptions of Lambertian reflection and static illumination, the task can be posed as a vari...
Alper Ayvaci, Michalis Raptis, Stefano Soatto
DAGM
2006
Springer
13 years 11 months ago
Segmentation-Based Motion with Occlusions Using Graph-Cut Optimization
Abstract. We propose to tackle the optical flow problem by a combination of two recent advances in the computation of dense correspondences, namely the incorporation of image segme...
Michael Bleyer, Christoph Rhemann, Margrit Gelautz
CDC
2009
IEEE
110views Control Systems» more  CDC 2009»
13 years 5 months ago
Perturbation analysis and optimization of multiclass multiobjective Stochastic Flow Models
Stochastic Flow Models (SFMs) are stochastic ystems that abstract the dynamics of complex discrete event systems involving the control of sharable resources. SFMs have been used to...
Chen Yao, Christos G. Cassandras