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Reseach Article

Robust Real-Time Stereoscopic Alignment

by Ross S Davies, Ian David Wilson, andrew Ware
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 81 - Number 19
Year of Publication: 2013
Authors: Ross S Davies, Ian David Wilson, andrew Ware
10.5120/14269-0220

Ross S Davies, Ian David Wilson, andrew Ware . Robust Real-Time Stereoscopic Alignment. International Journal of Computer Applications. 81, 19 ( November 2013), 7-15. DOI=10.5120/14269-0220

@article{ 10.5120/14269-0220,
author = { Ross S Davies, Ian David Wilson, andrew Ware },
title = { Robust Real-Time Stereoscopic Alignment },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 81 },
number = { 19 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 7-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume81/number19/14269-0220/ },
doi = { 10.5120/14269-0220 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:27.598018+05:30
%A Ross S Davies
%A Ian David Wilson
%A andrew Ware
%T Robust Real-Time Stereoscopic Alignment
%J International Journal of Computer Applications
%@ 0975-8887
%V 81
%N 19
%P 7-15
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a method for non-computationally expensive automatic alignment of cameras that utilises stereoscopic imagery separated at varying distances just below that of the intraocular distance. Here, automatic stereoscopic alignment in real-time is a non-trivial process that relies on calculating the best virtual alignment of camera lenses through image overlaying. This is important as retail 3D camera lenses are typically not sufficiently calibrated for accurate estimates of distance. The alignment of images allows the filtering of background objects and focuses on points of interest. Imprecision in camera lens calibration leads to problems with the required alignment of images and consequent filtering of background objects. The algorithm presented in this paper allows virtual calibration within non-calibrated cameras to provide a real-time filtering of images and the consequent identification of points of interest. The proposed method is capable of generating the best alignment setup at a reasonable computational expense in natural environments with partial background occlusion.

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Index Terms

Computer Science
Information Sciences

Keywords

Computer vision Stereoscopic calibration Stereoscopic vision