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» Markov Random Field Modeling in Computer Vision
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ICPR
2010
IEEE
13 years 7 months ago
A Novel Approach to Detect Ship-Radiated Signal Based on HMT
In the presence of non-gaussian noise, we propose a method for the detection of underwater shipradiated signal. The wavelet decomposition of the underwater signal yields a natural...
Yue Zhou, Zhibin Niu, Chenghao Wang
ICCV
2003
IEEE
14 years 11 months ago
Bayesian Clustering of Optical Flow Fields
We present a method for unsupervised learning of classes of motions in video. We project optical flow fields to a complete, orthogonal, a-priori set of basis functions in a probab...
Jesse Hoey, James J. Little
ICCV
2011
IEEE
12 years 9 months ago
A Nonparametric Riemannian Framework on Tensor Field with Application to Foreground Segmentation
Background modelling on tensor field has recently been proposed for foreground detection tasks. Taking into account the Riemannian structure of the tensor manifold, recent resear...
Rui Caseiro, João F. Henriques, Pedro Martins, Jo...
CVPR
2008
IEEE
14 years 11 months ago
One step beyond histograms: Image representation using Markov stationary features
This paper proposes a general framework called Markov stationary features (MSF) to extend histogram based features. The MSF characterizes the spatial co-occurrence of histogram pa...
Jianguo Li, Weixin Wu, Tao Wang, Yimin Zhang
CVPR
2007
IEEE
14 years 3 months ago
Multiple Target Tracking Using Spatio-Temporal Markov Chain Monte Carlo Data Association
We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Qian Yu, Gérard G. Medioni, Isaac Cohen