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 
             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 = "Oct. 29 - Nov. 1, 2018",
             language = "en",
                  ibi = "8JMKD3MGPAW/3S399DP",
                  url = "",
           targetfile = "WTD.pdf",
        urlaccessdate = "2020, Dec. 04"