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» Bayesian 3D Modeling from Images Using Multiple Depth Maps
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CVPR
2005
IEEE
15 years 11 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»
14 years 9 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
15 years 11 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
15 years 10 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
15 years 11 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