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» Markov Random Field Modeling in Computer Vision
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ICCV
2001
IEEE
14 years 11 months ago
Very High Accuracy Velocity Estimation using Orientation Tensors Parametric Motion and Simultaneous Segmentation of the Motion F
In [10] we presented a new velocity estimation algorithm, using orientation tensors and parametric motion models to provide both fast and accurate results. One of the tradeoffs be...
Gunnar Farnebäck
ICC
2007
IEEE
160views Communications» more  ICC 2007»
14 years 3 months ago
Efficient Coverage Planning for Grid-Based Wireless Sensor Networks
- In this paper we study efficient triangular grid-based sensor deployment planning for coverage when sensor placements are perturbed by random errors around their corresponding gr...
Glen Takahara, Kenan Xu, Hossam S. Hassanein
JCP
2008
114views more  JCP 2008»
13 years 9 months ago
Statistical Analysis and Data Analysis of Stock Market by Interacting Particle Models
The statistical analysis of Chinese stock market fluctuations modeled by the interacting particle systems has been done in this paper. The contact model and voter model of the inte...
Jun Wang, Bingli Fan, Tiansong Wang
CRV
2009
IEEE
237views Robotics» more  CRV 2009»
14 years 3 months ago
SEC: Stochastic Ensemble Consensus Approach to Unsupervised SAR Sea-Ice Segmentation
The use of synthetic aperture radar (SAR) has become an integral part of sea-ice monitoring and analysis in the polar regions. An important task in sea-ice analysis is to segment ...
Alexander Wong, David A. Clausi, Paul W. Fieguth
CVPR
2009
IEEE
15 years 3 months ago
D - Clutter: Building object model library from unsupervised segmentation of cluttered scenes
Autonomous systems which learn and utilize a limited visual vocabulary have wide spread applications. Enabling such systems to segment a set of cluttered scenes into objects is ...
Chandra Kambhamettu, Dimitris N. Metaxas, Gowri So...