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ECCV
2008
Springer
14 years 7 months ago
Efficiently Learning Random Fields for Stereo Vision with Sparse Message Passing
As richer models for stereo vision are constructed, there is a growing interest in learning model parameters. To estimate parameters in Markov Random Field (MRF) based stereo formu...
Jerod J. Weinman, Lam Tran, Christopher J. Pal
ICML
2003
IEEE
14 years 6 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
CVPR
2006
IEEE
14 years 7 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...
AMDO
2010
Springer
13 years 3 months ago
Compatible Particles for Part-Based Tracking
Particle Filter methods are one of the dominant tracking paradigms due to its ability to handle non-gaussian processes, multimodality and temporal consistency. Traditionally, the e...
Brais Martínez, Marc Vivet, Xavier Binefa
CVPR
2007
IEEE
14 years 7 months ago
Topology matching for 3D video compression
This paper presents a new technique to reduce the storage cost of high quality 3D video. In 3D video [12], a sequence of 3D objects represents scenes in motion. Every frame is com...
Tony Tung, Francis Schmitt, Takashi Matsuyama