SeaTurtleID2022: A long-span dataset for reliable sea turtle re-identification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43972919" target="_blank" >RIV/49777513:23520/24:43972919 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21230/24:00377619
Result on the web
<a href="https://ieeexplore.ieee.org/document/10484106" target="_blank" >https://ieeexplore.ieee.org/document/10484106</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/WACV57701.2024.00699" target="_blank" >10.1109/WACV57701.2024.00699</a>

Result language
angličtina
Original language name
SeaTurtleID2022: A long-span dataset for reliable sea turtle re-identification
Original language description
This paper introduces the first public large-scale, long-span dataset with sea turtle photographs captured in the wild-SeaTurtleID2022. The dataset contains 8729 photographs of 438 unique individuals collected within 13 years, making it the longest-spanned dataset for animal re-identification. Each photograph includes various annotations, e.g., identity, encounter timestamp, and body parts segmentation masks. Instead of a standard ''random"split, the dataset allows for two realistic and ecologically motivated splits: (i) time-aware: a closed-set with training, validation, and test data from different days/years, and (ii) open-set: with new unknown individuals in test and validation sets. We show that time-aware splits are essential for benchmarking methods for re-identification, as random splits lead to performance overestimation. Furthermore, a baseline instance segmentation and re-identification performance over various body parts is provided. At last, an end-to-end system for sea turtle re-identification is proposed and evaluated. The proposed system based on Hybrid Task Cascade for head instance segmentation and ArcFace-trained feature-extractor achieved an accuracy of 86.8%.
Czech name
—
Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
ISBN
979-8-3503-1892-0
ISSN
2472-6737
e-ISSN
2642-9381
Number of pages
11
Pages from-to
7131-7141
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
Piscataway
Event location
Waikoloa, HI, USA
Event date
Jan 3, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001222964607028

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