Optimized registration based on an ant colony for markerless augmented reality systems

Accurate registration in augmented reality systems is essential to guarantee the visual consistency of the augmented environment. Although error in the virtual-real alignment is almost unavoidable, different approaches have been proposed to quantify and reduce such errors. However, many of the exist...

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Bibliographic Details
Published in:Dyna (Medellín, Colombia) Colombia), 2020-01, Vol.87 (212), p.259-266
Main Authors: Jaramillo-Rojas, Gloria Elena, Branch Bedoya, John William
Format: Article
Language:English
Subjects:
ant colony optimization
augmented reality
heuristic method
heurístico
markerless registration
meta
meta-heuristic method
método meta
optimización de colonias de hormigas
realidad aumentada
registro sin marcadores
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Summary:Accurate registration in augmented reality systems is essential to guarantee the visual consistency of the augmented environment. Although error in the virtual-real alignment is almost unavoidable, different approaches have been proposed to quantify and reduce such errors. However, many of the existing solutions require a lot of a priori information, or they only focus on camera calibration to guarantee good results in the registration. This article presents a heuristic method that aims to reduce registration errors in markerless augmented reality systems. The proposed solution sees error reduction as a mono-objective optimization problem, which is addressed by means of the Ant Colony Optimization (ACO) algorithm. Experimental results reveal the validity of the proposed method, reaching an average error of 1.49 pixels for long video sequences.
ISSN:0012-7353
2346-2183
DOI:10.15446/dyna.v87n212.84039