Uma metodologia automática para geração de mapas de disparidades de ambientes reais
The objective of this work was the analysis, combination and adjustments of an algorithm set, in state-of-the-art, building a simple methodology, that is able to represent the depth of the elements in a scene, through the calculation of the disparity map. The map is automatically obtained, from real...
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| Tipo de recurso: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | Brasil |
| Institución: | Universidade Federal de São Carlos (UFSCAR) |
| Repositorio: | Repositório Institucional da UFSCAR |
| Idioma: | portugués |
| OAI Identifier: | oai:repositorio.ufscar.br:20.500.14289/9692 |
| Acceso en línea: | https://repositorio.ufscar.br/handle/20.500.14289/9692 |
| Access Level: | acceso abierto |
| Palabra clave: | Visão estéreo Matriz fundamental Mapa de disparidades Autocalibração Stereo vision Fundamental matrix Disparity map Autocalibration CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
| Sumario: | The objective of this work was the analysis, combination and adjustments of an algorithm set, in state-of-the-art, building a simple methodology, that is able to represent the depth of the elements in a scene, through the calculation of the disparity map. The map is automatically obtained, from real scenes, with minimal human intervention. Initially, the corners of the objects in a scene are obtained by the SURF algorithm in an image stereo pair, obtained from it. These corners are used to obtain a mapping from points in an image to its correspondences into another image, through a fundamental matrix (obtained by linear estimation, using Least Median of Squares or MSAC); later, the rectification and matching processes are done, generating the map, which suffers a post-processing to fix the distortions. The maps initially obtained was analysed in order to verify the processing time and the similarity with maps obtained by a manual method (which uses calibration). In the future, it is intended to use the studied algorithms as the basis for a system that will allow blind people to do spatial navigation tests in real environments |
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