Cited 213 time in
Calibration between Color Camera and 3D LIDAR Instruments with a Polygonal Planar Board
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Park, Yoonsu | - |
| dc.contributor.author | Yun, Seokmin | - |
| dc.contributor.author | Won, Chee Sun | - |
| dc.contributor.author | Cho, Kyungeun | - |
| dc.contributor.author | Um, Kyhyun | - |
| dc.contributor.author | Sim, Sungdae | - |
| dc.date.accessioned | 2024-09-25T03:31:18Z | - |
| dc.date.available | 2024-09-25T03:31:18Z | - |
| dc.date.issued | 2014-03 | - |
| dc.identifier.issn | 1424-8220 | - |
| dc.identifier.issn | 1424-3210 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/23594 | - |
| dc.description.abstract | Calibration between color camera and 3D Light Detection And Ranging (LIDAR) equipment is an essential process for data fusion. The goal of this paper is to improve the calibration accuracy between a camera and a 3D LIDAR. In particular, we are interested in calibrating a low resolution 3D LIDAR with a relatively small number of vertical sensors. Our goal is achieved by employing a new methodology for the calibration board, which exploits 2D-3D correspondences. The 3D corresponding points are estimated from the scanned laser points on the polygonal planar board with adjacent sides. Since the lengths of adjacent sides are known, we can estimate the vertices of the board as a meeting point of two projected sides of the polygonal board. The estimated vertices from the range data and those detected from the color image serve as the corresponding points for the calibration. Experiments using a low-resolution LIDAR with 32 sensors show robust results. | - |
| dc.format.extent | 21 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | MDPI | - |
| dc.title | Calibration between Color Camera and 3D LIDAR Instruments with a Polygonal Planar Board | - |
| dc.type | Article | - |
| dc.publisher.location | 스위스 | - |
| dc.identifier.doi | 10.3390/s140305333 | - |
| dc.identifier.scopusid | 2-s2.0-84896465103 | - |
| dc.identifier.wosid | 000336783300079 | - |
| dc.identifier.bibliographicCitation | SENSORS, v.14, no.3, pp 5333 - 5353 | - |
| dc.citation.title | SENSORS | - |
| dc.citation.volume | 14 | - |
| dc.citation.number | 3 | - |
| dc.citation.startPage | 5333 | - |
| dc.citation.endPage | 5353 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | Y | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Chemistry | - |
| dc.relation.journalResearchArea | Engineering | - |
| dc.relation.journalResearchArea | Instruments & Instrumentation | - |
| dc.relation.journalWebOfScienceCategory | Chemistry, Analytical | - |
| dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
| dc.relation.journalWebOfScienceCategory | Instruments & Instrumentation | - |
| dc.subject.keywordPlus | EXTRINSIC CALIBRATION | - |
| dc.subject.keywordAuthor | camera calibration | - |
| dc.subject.keywordAuthor | 3D LIDAR | - |
| dc.subject.keywordAuthor | sensor fusion | - |
| dc.subject.keywordAuthor | calibration board | - |
| dc.subject.keywordAuthor | 3D point clouds | - |
| dc.subject.keywordAuthor | calibration matrix | - |
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