Identificação de pontos robustos em marcadores naturais e aplicação de metodologia baseada em aprendizagem situada no desenvolvimento de sistemas de realidade aumentada

Imagem de Miniatura
Tipo
Tese
Data
2015-08-07
Autores
Forte, Cleberson Eugenio
Orientador
Marengoni, Maurício
Título da Revista
ISSN da Revista
Título de Volume
Membros da banca
Silveira, Ismar Frango
Kirner, Claudio
Concilio, Ilana de Almeida Souza
Thomaz, Carlos Eduardo
Programa
Engenharia Elétrica
Resumo
In the past, the Augmented Reality (AR) required advanced technologies in special devices for interaction and visualization. Nowadays, with the emergence of the mobile devices it has become common the usage of these tools in the development of AR systems applied to various purposes, including education, using natural markers. As the quality of images captured by mobile devices has increased the number of detected feature points has increased also, which ultimately hampers, or even prevents the technique to be used in applications, which run in real time. In addition, it becomes clear the necessity of proposing methodologies to be used in the development of educational applications using AR systems in order to improve the user s experience as well as the longevity of these applications, adding elements based on educational theories. The technique presented in this work determine illumination robust feature points, in order to reduce the time required to match high-resolution images. Additionally, the research also provides a conceptual framework methodology that, based on situated learning theory, combines the educational and technological aspects related to the context of developing mobile AR applications. Based on the experiments, it is possible to say that the technique using robust feature points saves about 70% in the processing time for matching high resolution images.
Descrição
Palavras-chave
visão computacional , pontos de interesse , realidade aumentada , computer vision , feature points , augmented reality
Citação
FORTE, Cleberson Eugenio. Identificação de pontos robustos em marcadores naturais e aplicação de metodologia baseada em aprendizagem situada no desenvolvimento de sistemas de realidade aumentada. 2015. 117 f. Tese (Doutorado em Engenharia Elétrica) - Universidade Presbiteriana Mackenzie, São Paulo, 2015.