Titulo:
A New Corner Detector Approach for Occupancy Grid Map Merging
.
Sumario:
The problem of merging maps in SLAM is one of the most studied in this field, because it allows to extend the SLAM algorithms to Multi-SLAM field. This issue is treated as a problem of merging images. In computer vision, merging images issue, nowadays it has many approaches for solving it, using feature extractors and descriptors. In this paper, we propose and show a new corner detector technique that can be used in map images. The results obtained in our tests show that, our corner detector is reliable and efficient to extract features in images generated by SLAM algorithms. Furthermore, we compared our algorithm with others feature detectors like Harris Corner Detector, Shi-Tomasi Detector, among others. We found out our corner detector h... Ver más
Guardado en:
2015-12-13
info:eu-repo/semantics/openAccess
http://purl.org/coar/access_right/c_abf2
| id |
metarevistapublica_eia_memorias_2_article_816 |
|---|---|
| record_format |
ojs |
| spelling |
A New Corner Detector Approach for Occupancy Grid Map Merging A New Corner Detector Approach for Occupancy Grid Map Merging The problem of merging maps in SLAM is one of the most studied in this field, because it allows to extend the SLAM algorithms to Multi-SLAM field. This issue is treated as a problem of merging images. In computer vision, merging images issue, nowadays it has many approaches for solving it, using feature extractors and descriptors. In this paper, we propose and show a new corner detector technique that can be used in map images. The results obtained in our tests show that, our corner detector is reliable and efficient to extract features in images generated by SLAM algorithms. Furthermore, we compared our algorithm with others feature detectors like Harris Corner Detector, Shi-Tomasi Detector, among others. We found out our corner detector has a good and reliable performance, doing the extraction from those kinds of map images. Velásquez Hernández, Carlos Alberto Prieto Ortiz, Flavio Augusto Corner Detectors Feature Detector Computer Vision Occupancy Grid Map , Año 2015 : IV Congreso Internacional de Ingeniería Mecatrónica y Automatización - CIIMA 2015 Artículo de revista Journal article 2015-12-13 00:00:00 2015-12-13 00:00:00 2015-12-13 application/pdf Memorias Memorias https://revistas.eia.edu.co/index.php/mem/article/view/816 https://revistas.eia.edu.co/index.php/mem/article/view/816 spa https://creativecommons.org/licenses/by-nc-sa/4.0/ https://revistas.eia.edu.co/index.php/mem/article/download/816/733 info:eu-repo/semantics/article http://purl.org/coar/resource_type/c_6501 http://purl.org/redcol/resource_type/ARTREF info:eu-repo/semantics/publishedVersion http://purl.org/coar/version/c_970fb48d4fbd8a85 info:eu-repo/semantics/openAccess http://purl.org/coar/access_right/c_abf2 Text Publication |
| institution |
UNIVERSIDAD EIA |
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https://nuevo.metarevistas.org/UNIVERSIDADEIA/logo.png |
| country_str |
Colombia |
| collection |
Memorias |
| title |
A New Corner Detector Approach for Occupancy Grid Map Merging |
| spellingShingle |
A New Corner Detector Approach for Occupancy Grid Map Merging Velásquez Hernández, Carlos Alberto Prieto Ortiz, Flavio Augusto Corner Detectors Feature Detector Computer Vision Occupancy Grid Map |
| title_short |
A New Corner Detector Approach for Occupancy Grid Map Merging |
| title_full |
A New Corner Detector Approach for Occupancy Grid Map Merging |
| title_fullStr |
A New Corner Detector Approach for Occupancy Grid Map Merging |
| title_full_unstemmed |
A New Corner Detector Approach for Occupancy Grid Map Merging |
| title_sort |
new corner detector approach for occupancy grid map merging |
| title_eng |
A New Corner Detector Approach for Occupancy Grid Map Merging |
| description |
The problem of merging maps in SLAM is one of the most studied in this field, because it allows to extend the SLAM algorithms to Multi-SLAM field. This issue is treated as a problem of merging images. In computer vision, merging images issue, nowadays it has many approaches for solving it, using feature extractors and descriptors. In this paper, we propose and show a new corner detector technique that can be used in map images. The results obtained in our tests show that, our corner detector is reliable and efficient to extract features in images generated by SLAM algorithms. Furthermore, we compared our algorithm with others feature detectors like Harris Corner Detector, Shi-Tomasi Detector, among others. We found out our corner detector has a good and reliable performance, doing the extraction from those kinds of map images.
|
| author |
Velásquez Hernández, Carlos Alberto Prieto Ortiz, Flavio Augusto |
| author_facet |
Velásquez Hernández, Carlos Alberto Prieto Ortiz, Flavio Augusto |
| topicspa_str_mv |
Corner Detectors Feature Detector Computer Vision Occupancy Grid Map |
| topic |
Corner Detectors Feature Detector Computer Vision Occupancy Grid Map |
| topic_facet |
Corner Detectors Feature Detector Computer Vision Occupancy Grid Map |
| citationedition |
, Año 2015 : IV Congreso Internacional de Ingeniería Mecatrónica y Automatización - CIIMA 2015 |
| publisher |
Memorias |
| ispartofjournal |
Memorias |
| source |
https://revistas.eia.edu.co/index.php/mem/article/view/816 |
| language |
spa |
| format |
Article |
| rights |
https://creativecommons.org/licenses/by-nc-sa/4.0/ info:eu-repo/semantics/openAccess http://purl.org/coar/access_right/c_abf2 |
| type_driver |
info:eu-repo/semantics/article |
| type_coar |
http://purl.org/coar/resource_type/c_6501 |
| type_version |
info:eu-repo/semantics/publishedVersion |
| type_coarversion |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| type_content |
Text |
| publishDate |
2015-12-13 |
| date_accessioned |
2015-12-13 00:00:00 |
| date_available |
2015-12-13 00:00:00 |
| url |
https://revistas.eia.edu.co/index.php/mem/article/view/816 |
| url_doi |
https://revistas.eia.edu.co/index.php/mem/article/view/816 |
| url2_str_mv |
https://revistas.eia.edu.co/index.php/mem/article/download/816/733 |
| _version_ |
1811200283252883456 |