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» Feature Correspondence: A Markov Chain Monte Carlo Approach
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JSAC
2008
102views more  JSAC 2008»
13 years 5 months ago
Convergence of Markov-Chain Monte-Carlo Approaches to Multiuser and MIMO Detection
Markov-chain Monte
Soren J. Henriksen, Brett Ninness, Steven R. Welle...
CVPR
2000
IEEE
14 years 7 months ago
Structure from Motion without Correspondence
A method is presented to recover 3D scene structure and camera motion from multiple images without the need for correspondence information. The problem is framed as finding the ma...
Frank Dellaert, Steven M. Seitz, Charles E. Thorpe...
PRL
2006
163views more  PRL 2006»
13 years 5 months ago
3D target recognition using cooperative feature map binding under Markov Chain Monte Carlo
A robust and effective feature map integration method is presented for infrared (IR) target recognition. Noise in an IR image makes a target recognition system unstable in pose es...
Sungho Kim, In-So Kweon
CVPR
2009
IEEE
14 years 3 months ago
Markov Chain Monte Carlo Combined with Deterministic Methods for Markov Random Field Optimization
Many vision problems have been formulated as en- ergy minimization problems and there have been signif- icant advances in energy minimization algorithms. The most widely-used energ...
Wonsik Kim (Seoul National University), Kyoung Mu ...
WACV
2005
IEEE
13 years 10 months ago
Dynamic Human Pose Estimation using Markov Chain Monte Carlo Approach
This paper addresses the problem of tracking human body pose in monocular video including automatic pose initialization and re-initialization after tracking failures caused by par...
Mun Wai Lee, Ramakant Nevatia