Document Type
Article
Date
7-29-2019
Keywords
Correspondence problem; Binocular matching; False matches; Symmetry; Depth detection.
Language
English
Funder(s)
National Science Foundation; Mabel E. Lewis Fund
Funding ID
Grant Number NSF BCS-1257096
Disciplines
Biomedical Engineering and Bioengineering
Description/Abstract
This record provides data from random-dot stereograms to use in solving the binocular correspondence problem through false-match symmetry. It also provides an implementation of the algorithm used in the article ‘Solving the stereo correspondence problem with false matches’ [Ng CJ, Farell B (2019) Solving the stereo correspondence problem with false matches. PLoSONE 14(7): e0219052. https://doi.org/10.1371/journal.pone.0219052].
The record consists of two parts, Data and Algorithm Demo. The Data component consists of pre-computed Keplerian arrays of all possible matches between filtered random-dot image pairs containing stereoscopically defined surfaces. The Algorithm Demo allows data files to be computed afresh from supplied pairs of images of various surface configurations. Plotting of data is possible in both cases. An interactive demo can also be used to explore the target image selection process.
Recommended Citation
Ng CJ, Farell B (2019) Solving the stereo correspondence problem with false matches. PLoSONE 14(7): e0219052. https://doi.org/10.1371/journal.pone.0219052 Data for this article can be found at: 10.5281/zenodo.3334347
Source
submission
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Rights
This data is licensed CCBY Attribution 4.0
