Cart (Loading....) | Create Account
Close category search window
 

A probabilistic framework for surface reconstruction from multiple images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Agrawal, M. ; Dept. of Comput. Sci., Maryland Univ., College Park, MD, USA ; Davis, L.S.

The paper presents a novel probabilistic framework for 3D surface reconstruction from multiple stereo images. The method works on a discrete voxelized representation of the scene. An iterative scheme is used to estimate the probability that a scene point lies on the true 3D surface. The novelty of our approach lies in the ability to model and recover surfaces which may be occluded in some views. This is done by explicitly estimating the probabilities that a 3D scene point is visible in a particular view from the set of given images. This relies on the fact that for a point on a lambertian surface, if the pixel intensities of its projection along two views differ, then the point is necessarily occluded in one of the views. We present results of surface reconstruction from both real and synthetic image sets.

Published in:

Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on  (Volume:2 )

Date of Conference:

2001

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.