A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee
- Submitting institution
-
The University of Sheffield
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2433
- Type
- D - Journal article
- DOI
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10.1371/journal.pcbi.1004887
- Title of journal
- PLoS Computational Biology
- Article number
- e1004887
- First page
- -
- Volume
- 12
- Issue
- 5
- ISSN
- 1553-734X
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2016
- 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
-
4
- Research group(s)
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B - Complex Systems Modelling
- Citation count
- 14
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper reverse-engineers the honeybee early visual system and its role in optic flow (visual motion) estimation. This is an important problem for computer vision and robotics, and the solution derived here is very robust and efficient, outperforming traditional computer vision and machine learning approaches in accuracy and computational efficiency. It has subsequently been patented (PCT/GB2018/051232), tested in flying robots, and is currently at the core of the technology stack of a University spin-out in AI and robotics, Opteran Technologies (www.opteran.com), which just completed its £2.1m seed funding raise (https://www.uktech.news/news/opteran-bags-2-1m-funding-to-control-autonomous-vehicles-20201124/).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -