Automated Visual Fin Identification of Individual Great White Sharks
- Submitting institution
-
University of Bristol
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 92129138
- Type
- D - Journal article
- DOI
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10.1007/s11263-016-0961-y
- Title of journal
- International Journal of Computer Vision
- Article number
- -
- First page
- 542
- Volume
- 122
- Issue
- 3
- ISSN
- 0920-5691
- Open access status
- Compliant
- Month of publication
- October
- 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
-
1
- Research group(s)
-
C - Visual Information Lab
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper describes the first fully automated biometric ID system for individual animals based on visual body contours. This IJCV paper significantly extends our BMVC’15 paper (DOI:10.5244/C.29.92), one of the Top10 BMVC2015 publications selected. The work was collaborative with NGO SaveOurSeas Foundation (SoSF) [https://saveourseas.com], who subsequently employed Hughes to extend and apply this work. As foreshadowed in the New Scientist (www.newscientist.com/article/2108232), the system has now been exploited at large scale (150,000+ fin photographs) by SoSF. The paper has formed the algorithmic backbone for research by other groups identifying individuals in species such as dolphins and whales (e.g. DOI:10.1109/ICCVW.2017.334).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -