Abstract
We present a new approach for constructing the 3D panorama for an indoor environment by joining together aligned submaps. For each submap, the trajectory of the moving camera is estimated based on the Kanade-Lucas-Tomasi (KLT) features. Our method can update the feature set status by adding new features and removing expiring ones adaptively to accommodate scene changes. The accuracy of the estimated poses is further improved through sparse bundle adjustment. Furthermore, we utilize a linear optimization framework to align all submaps to obtain a consistently extended 3D panorama and to refine the visual odometry at the same time. We evaluated our approach on publicly available benchmark datasets. The experiments demonstrate that the proposed method achieves low translational drift and is robust even when the camera moves very fast.
| Original language | English (US) |
|---|---|
| Title of host publication | 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1611-1615 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781479999880 |
| DOIs | |
| State | Published - May 18 2016 |
| Event | 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China Duration: Mar 20 2016 → Mar 25 2016 |
Publication series
| Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
|---|---|
| Volume | 2016-May |
| ISSN (Print) | 1520-6149 |
Other
| Other | 41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 |
|---|---|
| Country | China |
| City | Shanghai |
| Period | 3/20/16 → 3/25/16 |
Fingerprint
Keywords
- RGB-D camera
- SLAM
- linear optimization
- visual odometry
ASJC Scopus subject areas
- Software
- Signal Processing
- Electrical and Electronic Engineering
Cite this
3D panorama reconstruction based on sitemap joining. / Wang, Huixuan; Guo, Yanwen; Do, Minh N.; Zhang, Caiming; Tu, Changhe.
2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1611-1615 7471949 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2016-May).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - 3D panorama reconstruction based on sitemap joining
AU - Wang, Huixuan
AU - Guo, Yanwen
AU - Do, Minh N.
AU - Zhang, Caiming
AU - Tu, Changhe
PY - 2016/5/18
Y1 - 2016/5/18
N2 - We present a new approach for constructing the 3D panorama for an indoor environment by joining together aligned submaps. For each submap, the trajectory of the moving camera is estimated based on the Kanade-Lucas-Tomasi (KLT) features. Our method can update the feature set status by adding new features and removing expiring ones adaptively to accommodate scene changes. The accuracy of the estimated poses is further improved through sparse bundle adjustment. Furthermore, we utilize a linear optimization framework to align all submaps to obtain a consistently extended 3D panorama and to refine the visual odometry at the same time. We evaluated our approach on publicly available benchmark datasets. The experiments demonstrate that the proposed method achieves low translational drift and is robust even when the camera moves very fast.
AB - We present a new approach for constructing the 3D panorama for an indoor environment by joining together aligned submaps. For each submap, the trajectory of the moving camera is estimated based on the Kanade-Lucas-Tomasi (KLT) features. Our method can update the feature set status by adding new features and removing expiring ones adaptively to accommodate scene changes. The accuracy of the estimated poses is further improved through sparse bundle adjustment. Furthermore, we utilize a linear optimization framework to align all submaps to obtain a consistently extended 3D panorama and to refine the visual odometry at the same time. We evaluated our approach on publicly available benchmark datasets. The experiments demonstrate that the proposed method achieves low translational drift and is robust even when the camera moves very fast.
KW - RGB-D camera
KW - SLAM
KW - linear optimization
KW - visual odometry
UR - http://www.scopus.com/inward/record.url?scp=84973295076&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84973295076&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2016.7471949
DO - 10.1109/ICASSP.2016.7471949
M3 - Conference contribution
AN - SCOPUS:84973295076
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 1611
EP - 1615
BT - 2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -