Learning Spatial Relationships From 3D Vision Using Histograms
- Submitting institution
-
University of Aberdeen
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 70686310
- Type
- E - Conference contribution
- DOI
-
10.1109/ICRA.2014.6906902
- Title of conference / published proceedings
- 2014 IEEE International Conference on Robotics and Automation (ICRA)
- First page
- 501
- Volume
- -
- Issue
- -
- ISSN
- 1050-4729
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2014
- URL
-
-
- 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
-
5
- Research group(s)
-
-
- Citation count
- 5
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The paper reports on Fichtl’s PhD research, supervised by Guerin. It is significant because it presents one of the few approaches to tackle affordances determined by the relationship among two objects in the environment. It does so using a novel histogram feature successfully extended in further publications. The approach was applied in the EU FP7 Xperience project (Fichtl was a post-doc in the project) to determine how robot knowledge can be bootstrapped through experience. Guerin was heavily involved in writing the paper and designing experiments.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
