Indexing 3D scenes using the interaction bisector surface
- Submitting institution
-
The University of Leeds
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- UOA11-3603
- Type
- D - Journal article
- DOI
-
10.1145/2574860
- Title of journal
- ACM Transactions on Graphics (TOG)
- Article number
- 22
- First page
- -
- Volume
- 33
- Issue
- 3
- ISSN
- 0730-0301
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- 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
-
2
- Research group(s)
-
D - CSE (Computational Science and Engineering)
- Citation count
- 38
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Having proposed the first approach of its kind, this paper started a new sub-field then, machine-learning based on 3D scene analysis and synthesis, in computer graphics. Since published, there has been many following papers in different fields such as computer graphics (doi.org/10.1145/2988458.2988473, doi.org/10.1145/3306346.3322961) and robotics (doi.org/10.3389/fnbot.2020.00045) in internationally leading journals. As a TOG paper it was invited for presentation at SIGGRAPH 2014. Invited research talks at universities (Bath, Sheffield) and follow-on research funding (~£84K, Strategic Priorities Fund Research England; Nvidia GPU grant).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
