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» An Attentional Framework for Stereo Vision
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CVPR
2010
IEEE
15 years 6 months ago
A Framework for Ultra High Resolution 3D Imaging
We present an imaging framework to acquire 3D surface scans at ultra high-resolutions (exceeding 600 samples per mm2 ). Our approach couples a standard structured-light setup and ...
Zheng Lu, Yu-Wing Tai, Moshe Ben-Ezra, Michael Bro...
SCALESPACE
2009
Springer
15 years 4 months ago
Generic Scene Recovery Using Multiple Images
In this paper, a generative model based method for recovering both the shape and the reflectance of the surface(s) of a scene from multiple images is presented, assuming that illu...
Kuk-Jin Yoon, Emmanuel Prados, Peter F. Sturm
CVIU
2007
154views more  CVIU 2007»
14 years 9 months ago
Bayesian stereo matching
A Bayesian framework is proposed for stereo vision where solutions to both the model parameters and the disparity map are posed in terms of predictions of latent variables, given ...
Li Cheng, Terry Caelli
WAPCV
2004
Springer
15 years 3 months ago
TarzaNN: A General Purpose Neural Network Simulator for Visual Attention Modeling
A number of computational models of visual attention exist, but making comparisons is difficult due to the incompatible implementations and levels at which the simulations are con...
Albert L. Rothenstein, Andrei Zaharescu, John K. T...
CVPR
2005
IEEE
15 years 12 months ago
Geo-Consistency for Wide Multi-Camera Stereo
This paper presents a new model to overcome the occlusion problems coming from wide baseline multiple camera stereo. Rather than explicitly modeling occlusions in the matching cos...
Marc-Antoine Drouin, Martin Trudeau, Sébast...