By Topic

Generating Dense Point Correspondence Ground-Truth across Multiple Views

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)
Usumezbas, A. ; Sch. of Eng., Brown Univ., Providence, RI, USA ; Kimia, B.

A ground truth dataset representing dense point correspondences across multiple views is useful in evaluating algorithms in a range of multiview geometry applications. Common datasets sparsely label point correspondences across views by either hand-marking corresponding points or by using identifiable fiducials in the scene. A few datasets feature dense correspondences but these have significant drawbacks: (i) methods using camera calibration and a laser scanner result in significant correspondence errors due to inaccurate depth estimates, (ii) methods using structured light can suffer from imaging artifacts or limitations. In addition, most of these datasets have only limited horizontal translation, not depicting wide-baseline challenges such as occlusion and intensity variations. We propose a probabilistic framework using a structured light approach where the likelihood of pixel correspondences is measured. We show that a logarithmic representation of ratios of images is the proper domain to assess the likelihood that an image pixel corresponds to a given illumination pattern. The result is a probabilistic dense correspondence map which can be used for evaluating multiview algorithms. We have created a dataset containing 13 high resolution images of a complex scene taken from distinct views which is lit using three different projectors. The resulting multi-view correspondence will be made available for public use.

Published in:

3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2012 Second International Conference on

Date of Conference:

13-15 Oct. 2012