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» Markov Random Field Modeling in Computer Vision
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CVPR
2008
IEEE
14 years 11 months ago
Max Margin AND/OR Graph learning for parsing the human body
We present a novel structure learning method, Max Margin AND/OR Graph (MM-AOG), for parsing the human body into parts and recovering their poses. Our method represents the human b...
Long Zhu, Yuanhao Chen, Yifei Lu, Chenxi Lin, Alan...
JMLR
2010
115views more  JMLR 2010»
13 years 4 months ago
Polynomial-Time Exact Inference in NP-Hard Binary MRFs via Reweighted Perfect Matching
We develop a new form of reweighting (Wainwright et al., 2005b) to leverage the relationship between Ising spin glasses and perfect matchings into a novel technique for the exact ...
Nic Schraudolph
BMCV
2000
Springer
14 years 1 months ago
Front-End Vision: A Multiscale Geometry Engine
The paper is a short tutorial on the multiscale differential geometric possibilities of the front-end visual receptive fields, modeled by Gaussian derivative kernels. The paper is ...
Bart M. ter Haar Romeny, Luc Florack
ICCV
2005
IEEE
14 years 11 months ago
Incorporating Visual Knowledge Representation in Stereo Reconstruction
In this paper, we present a two-layer generative model that incorporates generic middle-level visual knowledge for dense stereo reconstruction. The visual knowledge is represented...
Adrian Barbu, Song Chun Zhu
ICCV
2001
IEEE
14 years 11 months ago
Topology Free Hidden Markov Models: Application to Background Modeling
Hidden Markov Models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Th...
Bjoern Stenger, Visvanathan Ramesh, Nikos Paragios...