Abstract
This paper present a framework for incremental 3D cuboid modeling combined with RGB-D SLAM. While performing RGB-D SLAM, planes are incrementally reconstructed from point clouds. Then, cuboids are detected in the planes by analyzing the positional relationships between the planes; orthogonality, convexity, and proximity. Finally, the position, pose and size of a cuboid are determined by computing the intersection of three perpendicular planes. In addition, the cuboid shapes are incrementally updated to suppress false detections with sequential measurements. As an application of our framework, an augmented reality based interactive cuboid modeling system is introduced. In the evaluation at a cluttered environment, the precision and recall of the cuboid detection are improved with our framework owing to stable plane detection, compared with a batch based method.
| Original language | English |
|---|---|
| Title of host publication | Computer Vision – ECCV 2018 Workshops, Proceedings |
| Editors | Laura Leal-Taixé, Stefan Roth |
| Publisher | Springer Verlag |
| Pages | 414-429 |
| Number of pages | 16 |
| ISBN (Print) | 9783030110086 |
| DOIs | |
| Publication status | Published - Jan 1 2019 |
| Event | 15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany Duration: Sep 8 2018 → Sep 14 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11129 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 15th European Conference on Computer Vision, ECCV 2018 |
|---|---|
| Country | Germany |
| City | Munich |
| Period | 9/8/18 → 9/14/18 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
RGB-D SLAM based incremental cuboid modeling. / Mishima, Masashi; Uchiyama, Hideaki; Thomas, Diego Gabriel Francis; Taniguchi, Rin-Ichiro; Roberto, Rafael; Lima, João Paulo; Teichrieb, Veronica.
Computer Vision – ECCV 2018 Workshops, Proceedings. ed. / Laura Leal-Taixé; Stefan Roth. Springer Verlag, 2019. p. 414-429 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11129 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - RGB-D SLAM based incremental cuboid modeling
AU - Mishima, Masashi
AU - Uchiyama, Hideaki
AU - Thomas, Diego Gabriel Francis
AU - Taniguchi, Rin-Ichiro
AU - Roberto, Rafael
AU - Lima, João Paulo
AU - Teichrieb, Veronica
PY - 2019/1/1
Y1 - 2019/1/1
N2 - This paper present a framework for incremental 3D cuboid modeling combined with RGB-D SLAM. While performing RGB-D SLAM, planes are incrementally reconstructed from point clouds. Then, cuboids are detected in the planes by analyzing the positional relationships between the planes; orthogonality, convexity, and proximity. Finally, the position, pose and size of a cuboid are determined by computing the intersection of three perpendicular planes. In addition, the cuboid shapes are incrementally updated to suppress false detections with sequential measurements. As an application of our framework, an augmented reality based interactive cuboid modeling system is introduced. In the evaluation at a cluttered environment, the precision and recall of the cuboid detection are improved with our framework owing to stable plane detection, compared with a batch based method.
AB - This paper present a framework for incremental 3D cuboid modeling combined with RGB-D SLAM. While performing RGB-D SLAM, planes are incrementally reconstructed from point clouds. Then, cuboids are detected in the planes by analyzing the positional relationships between the planes; orthogonality, convexity, and proximity. Finally, the position, pose and size of a cuboid are determined by computing the intersection of three perpendicular planes. In addition, the cuboid shapes are incrementally updated to suppress false detections with sequential measurements. As an application of our framework, an augmented reality based interactive cuboid modeling system is introduced. In the evaluation at a cluttered environment, the precision and recall of the cuboid detection are improved with our framework owing to stable plane detection, compared with a batch based method.
UR - http://www.scopus.com/inward/record.url?scp=85061738490&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85061738490&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-11009-3_25
DO - 10.1007/978-3-030-11009-3_25
M3 - Conference contribution
SN - 9783030110086
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 414
EP - 429
BT - Computer Vision – ECCV 2018 Workshops, Proceedings
A2 - Leal-Taixé, Laura
A2 - Roth, Stefan
PB - Springer Verlag
ER -