Noise-resilient reconstruction of panoramas and 3D scenes using robot-mounted unsynchronized commodity RGB-D cameras
- Submitting institution
-
Cardiff University / Prifysgol Caerdydd
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 104749243
- Type
- D - Journal article
- DOI
-
10.1145/3389412
- Title of journal
- ACM Transactions on Graphics
- Article number
- 152
- First page
- -
- Volume
- 39
- Issue
- 5
- ISSN
- 0730-0301
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2020
- URL
-
https://doi.org/10.1145/3389412
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
6
- Research group(s)
-
V - Visual computing
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This collaboration with Tsinghua University, MIT, City University Hong Kong and RWTH Aachen University, proposes a novel noise-resilient technique for reconstruction of 3D panoramas and 3D scenes, using low-cost, unsynchronised RGB-D cameras installed on a robot platform, through effective regularisation and modelling of data uncertainty. The 3D panoramic fusion approach is particularly suitable for automated scanning as it simplifies robotic planning. The work was presented at ACM SIGGRAPH 2020.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -