Nontemporal Relative Pose Estimation for Opti-Acoustic Bundle Adjustment
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 권대현 | - |
dc.contributor.author | 신영식 | - |
dc.contributor.author | 김영지 | - |
dc.contributor.author | 이영준 | - |
dc.contributor.author | 최현택 | - |
dc.contributor.author | 김아영 | - |
dc.date.accessioned | 2021-12-08T12:41:08Z | - |
dc.date.available | 2021-12-08T12:41:08Z | - |
dc.date.issued | 20160919 | - |
dc.identifier.uri | https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/3756 | - |
dc.description.abstract | This paper presents the bundle adjustment (BA) between a sonar and optical image for an Opti-Acoustic sensor model. An Opti-Acoustic sensor model allows heterogeneous sensor fusion of an optical camera and acoustic sonar that have a mutualsupplementary relation. There are two challenges to the Opti-Acoustic method. First, it is difficult to guarantee a common view from the two significantly different sensor field of view. Second, it is tough to figure out the correspondences between the camera and sonar image, since those sensors have heterogeneous sensor geometries. This paper focuses on the first issue by proposing asynchronously applicable relative motion estimation via BA. For the second issue, we proposeusing a Dense Adaptive Self-Correlation Descriptor (DASC) to establish correspondences between an optical camera and a sonar image. The proposed Opti-Acoustic BA is validated through autonomous underwater vehicle (AUV) simultaneous localization and mapping (SLAM) in both simulated and real tank tests. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.title | Nontemporal Relative Pose Estimation for Opti-Acoustic Bundle Adjustment | - |
dc.title.alternative | Nontemporal Relative Pose Estimation for Opti-Acoustic Bundle Adjustment | - |
dc.type | Conference | - |
dc.citation.title | Oceans2016 | - |
dc.citation.volume | 1 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 1 | - |
dc.citation.endPage | 5 | - |
dc.citation.conferenceName | Oceans2016 | - |
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