Probabilistic account for multi-view stereo

author: Rik Fransens, ESAT-PSI/VISICS, KU Leuven
published: Feb. 25, 2007,   recorded: May 2004,   views: 3515
Categories

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

This paper describes a method for dense depth reconstruction from wide-baseline images. In a wide-baseline setting an inherent difficulty which complicates the stereo correspondence problem is self-occlusion. Also, we have to consider the possibility that image pixels in different images, which are projections of the same point in the scene, will have different colour values due to non-Lambertian effects or discretization errors. We propose a Bayesian approach to tackle these problems. In this framework, the images are regarded as noisy measurements of an underlying 'true' image-function. Also, the image data is considered incomplete, in the sense that we do not know which pixels from a particular image are occluded in the other images. We describe an EM-algorithm, which iterates between estimating values for all hidden quantities, and optimising the current depth estimates. The algorithm has few free parameters, displays a stable convergence behaviour and generates accurate depth estimates.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

Comment1 sleeman bazaw, September 28, 2009 at 5:08 p.m.:

Hi,
Is there any slides to this video lecture ??
thnx

Write your own review or comment:

make sure you have javascript enabled or clear this field: