Detalhes bibliográficos
| Ano de defesa: |
2017 |
| Autor(a) principal: |
Lopes, Lais Cândido Rodrigues da Silva
 |
| Orientador(a): |
Laureano, Gustavo Teodoro
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| Banca de defesa: |
Laureano, Gustavo Teodoro,
Soares, Fabrizzio Alphonsus Alves de Melo Nunes,
Gonçalves, Cristhiane |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
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| Programa de Pós-Graduação: |
Programa de Pós-graduação em Ciência da Computação (INF)
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| Departamento: |
Instituto de Informática - INF (RG)
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| País: |
Brasil
|
| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/7717
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Resumo: |
The capture of images by multiple positions allows to recover the three-dimensional information of the environment applying the knowledge about the geometry of the cameras and the correspondences between the points of the images. The correspondence of characteristics in images is the task of relating regions of different images to the same point of interest, being considered a problem of difficult solution, since it suffers with ambiguities, occlusions, variation of illumination, besides local distortions. For having so many challenges, this subject is one of the most investigated in the field of computer vision cite Scharstein2001. The present dissertation aims to generate dense disparity maps, using graph cutting, from search spaces constructed with matching metrics based on laws of the Gestalt theory. A hybrid approach was developed, consisting of a local algorithm to construct the image disparity space (EDI), and a global algorithm used to optimize the disparities. The results were maps of disparities close to the expected maps ( textit groundtruth). It was also perceived the best performance of the methodology proposed in relation to the separate methods that compose it. |
