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» On the Vulnerability of Large Graphs
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CVPR
2004
IEEE
15 years 12 months ago
Efficient Belief Propagation for Early Vision
Markov random field models provide a robust and unified framework for early vision problems such as stereo, optical flow and image restoration. Inference algorithms based on graph...
Pedro F. Felzenszwalb, Daniel P. Huttenlocher
CVPR
2005
IEEE
15 years 12 months ago
Digital Tapestry
This paper addresses the novel problem of automatically synthesizing an output image from a large collection of different input images. The synthesized image, called a digital tap...
Carsten Rother, Sanjiv Kumar, Vladimir Kolmogorov,...
CVPR
2006
IEEE
15 years 12 months ago
Solving Markov Random Fields using Second Order Cone Programming Relaxations
This paper presents a generic method for solving Markov random fields (MRF) by formulating the problem of MAP estimation as 0-1 quadratic programming (QP). Though in general solvi...
M. Pawan Kumar, Philip H. S. Torr, Andrew Zisserma...
CVPR
2008
IEEE
15 years 12 months ago
Globally optimal shape-based tracking in real-time
Most algorithms for real-time tracking of deformable shapes provide sub-optimal solutions for a suitable energy minimization task: The search space is typically considered too lar...
Thomas Schoenemann, Daniel Cremers
ICCV
2001
IEEE
15 years 11 months ago
Image Segmentation with Minimum Mean Cut
We introduce a new graph-theoretic approach to image segmentation based on minimizing a novel class of `mean cut' cost functions. Minimizing these cost functions corresponds ...
Song Wang, Jeffrey Mark Siskind