@InProceedings{JúniorSilvPaiv:2018:ViAuRe,
author = "J{\'u}nior, Daniel Lima Gomes and Silva, Arist{\'o}fanes Correa
and Paiva, Anselmo Cardoso de",
affiliation = "{Instituto Federal do Maranh{\~a}o} and {Universidade Federal do
Maranh{\~a}o} and {Universidade Federal do Maranh{\~a}o}",
title = "Virtual and Augmented Reality Applications Development Methodology
using natural markers in industrial scenarios",
booktitle = "Proceedings...",
year = "2018",
editor = "Ross, Arun and Gastal, Eduardo S. L. and Jorge, Joaquim A. and
Queiroz, Ricardo L. de and Minetto, Rodrigo and Sarkar, Sudeep and
Papa, Jo{\~a}o Paulo and Oliveira, Manuel M. and Arbel{\'a}ez,
Pablo and Mery, Domingo and Oliveira, Maria Cristina Ferreira de
and Spina, Thiago Vallin and Mendes, Caroline Mazetto and Costa,
Henrique S{\'e}rgio Gutierrez and Mejail, Marta Estela and Geus,
Klaus de and Scheer, Sergio",
organization = "Conference on Graphics, Patterns and Images, 31. (SIBGRAPI)",
publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
address = "Porto Alegre",
keywords = "Virtual Reality, Augmented Reality, Natural Markers, Haar-like
Features.",
abstract = "In this Ph.D. research, we have proposed a methodology for
development of Virtual Reality (VR) and Augmented Reality (AR)
applications, using natural markers for industrial scenarios. The
proposed methodology uses the object annotation concept and
visualization proposals are presented both for development of VR
as for AR environments. In VR environments, the methodology is
applied for object detection step of the semi-automatic authoring
tool. On the other hand, in AR environments, is presented the
concept of georeferenced natural markers, which use the
georeferenced data integrated with object detection process using
image processing techniques. The energy substations scenarios were
used as case study for both approaches. This work proposes using
Haar-like feature based natural markers integrated with
homomorphic filtering for object training and detection process.
The results enable the equipment detection at different points of
view, within the operating scenario. Besides that, in AR, it
enables the pose estimation in real-time using ORB features, while
in VR it enables the semi-automatic object detection, which are
used as information points for inclusion of virtual information.
Several industrial scenarios, and especially the energy sector,
has a high degree of complexity in the information processing and
visualization. In this sense, beyond the 3D natural markers
methodology, this work presents visualization applications for
industrial scenario visualization in VR and AR approaches.",
conference-location = "Foz do Igua{\c{c}}u, PR, Brazil",
conference-year = "29 Oct.-1 Nov. 2018",
language = "en",
ibi = "8JMKD3MGPAW/3S399DP",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3S399DP",
targetfile = "WTD.pdf",
urlaccessdate = "2024, Apr. 28"
}