Comparison between low-cost passive and active vision for obstacle depth
Obstacle detection is a key issue in many current applications, especially in applications that have been increasingly highlighted such as: advanced driver assistance systems (ADAS), simultaneous localization and mapping (SLAM) and autonomous navigation system. This can be achieved by active and pas...
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Universidade Federal de Roraima, Centro de Ciência e Tecnologia
2020-07-01
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doaj-cbdc462a11a844638a4f8acaeabcbebf2021-06-10T21:56:13ZporUniversidade Federal de Roraima, Centro de Ciência e TecnologiaRCT: Revista de Ciência e Tecnologia2447-70282020-07-01602358Comparison between low-cost passive and active vision for obstacle depthThiago Rateke0Vito Francisco Chiarella1Karla Aparecida Justen2Antonio Carlos Sobieranski3Sylvio Luiz Mantelli Neto4Eros Comunello5Aldo von Wangenheim6Postgraduate Program in Computer Science (PPFCC), Federal University of Santa Catarina (UFSC), Department of Informatics and Statistics.Graduate Program in Materials Science and Engineering (PGMAT). Federal University of Santa Catarina (UFSC).Image Processing and Computer Graphics Lab (LAPIX). National Institute for Digital Convergence (INCoD).Department of Computing. Federal University of Santa Catarina (UFSC).Image Processing and Computer Graphics Lab (LAPIX). National Institute for Digital Convergence (INCoD).Master in Applied Computing (MCA). University of Itajaí Valley (UNIVALI).Graduate Program in Computer Science (PPGCC). Federal University of Santa Catarina (UFSC). Department of Informatics and Statistics. Image Processing and Computer Graphics Lab (LAPIX). National Institute for Digital Convergence (INCoD).Obstacle detection is a key issue in many current applications, especially in applications that have been increasingly highlighted such as: advanced driver assistance systems (ADAS), simultaneous localization and mapping (SLAM) and autonomous navigation system. This can be achieved by active and passive acquisition vision systems, for example: laser and cameras respectively. In this paper we present a comparison between low-cost active and passive devices, more specifically LIDAR and two cameras. To this comparison a disparity map is created by stereo correspondence through two images and a point cloud map created by LIDAR data values (distances measures). The obtained results shown that passive vision can be as good as or even better than active vision in low cost scenarios.https://revista.ufrr.br/rct/article/view/5966 |
collection |
DOAJ |
language |
Portuguese |
format |
Article |
sources |
DOAJ |
author |
Thiago Rateke Vito Francisco Chiarella Karla Aparecida Justen Antonio Carlos Sobieranski Sylvio Luiz Mantelli Neto Eros Comunello Aldo von Wangenheim |
spellingShingle |
Thiago Rateke Vito Francisco Chiarella Karla Aparecida Justen Antonio Carlos Sobieranski Sylvio Luiz Mantelli Neto Eros Comunello Aldo von Wangenheim Comparison between low-cost passive and active vision for obstacle depth RCT: Revista de Ciência e Tecnologia |
author_facet |
Thiago Rateke Vito Francisco Chiarella Karla Aparecida Justen Antonio Carlos Sobieranski Sylvio Luiz Mantelli Neto Eros Comunello Aldo von Wangenheim |
author_sort |
Thiago Rateke |
title |
Comparison between low-cost passive and active vision for obstacle depth |
title_short |
Comparison between low-cost passive and active vision for obstacle depth |
title_full |
Comparison between low-cost passive and active vision for obstacle depth |
title_fullStr |
Comparison between low-cost passive and active vision for obstacle depth |
title_full_unstemmed |
Comparison between low-cost passive and active vision for obstacle depth |
title_sort |
comparison between low-cost passive and active vision for obstacle depth |
publisher |
Universidade Federal de Roraima, Centro de Ciência e Tecnologia |
series |
RCT: Revista de Ciência e Tecnologia |
issn |
2447-7028 |
publishDate |
2020-07-01 |
description |
Obstacle detection is a key issue in many current applications, especially in applications that have been increasingly highlighted such as: advanced driver assistance systems (ADAS), simultaneous localization and mapping (SLAM) and autonomous navigation system. This can be achieved by active and passive acquisition vision systems, for example: laser and cameras respectively. In this paper we present a comparison between low-cost active and passive devices, more specifically LIDAR and two cameras. To this comparison a disparity map is created by stereo correspondence through two images and a point cloud map created by LIDAR data values (distances measures). The obtained results shown that passive vision can be as good as or even better than active vision in low cost scenarios. |
url |
https://revista.ufrr.br/rct/article/view/5966 |
work_keys_str_mv |
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