%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2018/10.16.15.35
%2 sid.inpe.br/sibgrapi/2018/10.16.15.35.28
%T Virtual and Augmented Reality Applications Development Methodology using natural markers in industrial scenarios
%D 2018
%A Júnior, Daniel Lima Gomes,
%A Silva, Aristófanes Correa,
%A Paiva, Anselmo Cardoso de,
%@affiliation Instituto Federal do Maranhão
%@affiliation Universidade Federal do Maranhão
%@affiliation Universidade Federal do Maranhão
%E Ross, Arun,
%E Gastal, Eduardo S. L.,
%E Jorge, Joaquim A.,
%E Queiroz, Ricardo L. de,
%E Minetto, Rodrigo,
%E Sarkar, Sudeep,
%E Papa, João Paulo,
%E Oliveira, Manuel M.,
%E Arbeláez, Pablo,
%E Mery, Domingo,
%E Oliveira, Maria Cristina Ferreira de,
%E Spina, Thiago Vallin,
%E Mendes, Caroline Mazetto,
%E Costa, Henrique Sérgio Gutierrez,
%E Mejail, Marta Estela,
%E Geus, Klaus de,
%E Scheer, Sergio,
%B Conference on Graphics, Patterns and Images, 31 (SIBGRAPI)
%C Foz do Iguaçu, PR, Brazil
%8 29 Oct.-1 Nov. 2018
%I Sociedade Brasileira de Computação
%J Porto Alegre
%S Proceedings
%K Virtual Reality, Augmented Reality, Natural Markers, Haar-like Features.
%X 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.
%@language en
%3 WTD.pdf