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» Bayesian 3D Modeling from Images Using Multiple Depth Maps
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CVPR
2005
IEEE
14 years 6 months ago
Bayesian 3D Modeling from Images Using Multiple Depth Maps
This paper addresses the problem of reconstructing the geometry and color of a Lambertian scene, given some fully calibrated images acquired with wide baselines. In order to compl...
Pau Gargallo, Peter F. Sturm
PAMI
2008
161views more  PAMI 2008»
13 years 4 months ago
Multilayered 3D LiDAR Image Construction Using Spatial Models in a Bayesian Framework
Standard 3D imaging systems process only a single return at each pixel from an assumed single opaque surface. However, there are situations when the laser return consists of multip...
Sergio Hernandez-Marin, Andrew M. Wallace, Gavin J...
ICIP
2004
IEEE
14 years 6 months ago
Robust ego-motion estimation and 3d model refinement using depth based parallax model
We present an iterative algorithm for robustly estimating the egomotion and refining and updating a coarse, noisy and partial depth map using a depth based parallax model and brig...
Amit K. Agrawal, Rama Chellappa
ICPR
2006
IEEE
14 years 5 months ago
3D and Infrared Face Reconstruction from RGB data using Canonical Correlation Analysis
In this paper, we apply a multiple regression method based on Canonical Correlation Analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the corre...
Michael Reiter, Rene Donner, Georg Langs, Horst Bi...
ICIP
1999
IEEE
14 years 6 months ago
Realistic 3-D Scene Modeling from Uncalibrated Image Sequences
This contribution addresses the problem of obtaining photorealistic 3D models of a scene from images alone with a structure-from-motion approach. The 3D scene is observed from mul...
Reinhard Koch, Marc Pollefeys, Luc J. Van Gool