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» Modeling Image Textures by Gibbs Random Fields
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ICPR
2006
IEEE
15 years 6 months ago
A Conditional Random Field Model for Video Super-resolution
In this paper, we propose a learning-based method for video super-resolution. There are two main contributions of the proposed method. First, information from cameras with differe...
Dan Kong, Mei Han, Wei Xu, Hai Tao, Yihong Gong
104
Voted
IROS
2009
IEEE
165views Robotics» more  IROS 2009»
15 years 7 months ago
Autonomous altitude estimation of a UAV using a single onboard camera
Abstract— Autonomous estimation of the altitude of an Unmanned Aerial Vehicle (UAV) is extremely important when dealing with flight maneuvers like landing, steady flight, etc. ...
Anoop Cherian, Jonathan Andersh, Vassilios Morella...
ECCV
2004
Springer
16 years 2 months ago
Light Field Appearance Manifolds
Abstract. Statistical shape and texture appearance models are powerful image representations, but previously had been restricted to 2D or 3D shapes with smooth surfaces and lambert...
Chris Mario Christoudias, Louis-Philippe Morency, ...
ECCV
2006
Springer
16 years 2 months ago
Efficient Belief Propagation with Learned Higher-Order Markov Random Fields
Belief propagation (BP) has become widely used for low-level vision problems and various inference techniques have been proposed for loopy graphs. These methods typically rely on a...
Xiangyang Lan, Stefan Roth, Daniel P. Huttenlocher...
118
Voted
IJCV
2006
161views more  IJCV 2006»
15 years 17 days ago
Discriminative Random Fields
In this research we address the problem of classification and labeling of regions given a single static natural image. Natural images exhibit strong spatial dependencies, and mode...
Sanjiv Kumar, Martial Hebert