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ICIAP
2005
ACM
15 years 7 months ago
Markovian Energy-Based Computer Vision Algorithms on Graphics Hardware
This paper shows how Markovian segmentation algorithms used to solve well known computer vision problems such as motion estimation, motion detection and stereovision can be signiï¬...
Pierre-Marc Jodoin, Max Mignotte, Jean-Franç...
ECCV
2010
Springer
15 years 2 months ago
Fast and Exact Primal-Dual Iterations for Variational Problems in Computer Vision
The saddle point framework provides a convenient way to formulate many convex variational problems that occur in computer vision. The framework unifies a broad range of data and re...
Jan Lellmann, Dirk Breitenreicher, Christoph Schn&...
PAMI
2007
129views more  PAMI 2007»
15 years 1 months ago
Algorithmic Differentiation: Application to Variational Problems in Computer Vision
Abstract— Many vision problems can be formulated as minimization of appropriate energy functionals. These energy functionals are usually minimized, based on the calculus of varia...
Thomas Pock, Michael Pock, Horst Bischof
AIPR
2008
IEEE
15 years 3 months ago
Low-cost, high-speed computer vision using NVIDIA's CUDA architecture
In this paper, we introduce real time image processing techniques using modern programmable Graphic Processing Units (GPU). GPUs are SIMD (Single Instruction, Multiple Data) device...
Seung In Park, Sean P. Ponce, Jing Huang, Yong Cao...
CVPR
2000
IEEE
16 years 3 months ago
A General Method for Errors-in-Variables Problems in Computer Vision
The Errors-in-Variables (EIV) model from statistics is often employed in computer vision thoughonlyrarely under this name. In an EIV model all the measurements are corrupted by no...
Bogdan Matei, Peter Meer