The Saimaa ringed seal (Phoca hispida saimensis) is one of the most endangered seals in the world.
It is a symbol of Lake Saimaa and the Finnish nature conservation movement.
At present slightly under 400 ringed seals live in Lake Saimaa, and some 60 pups are born annually.
Recently animal biometrics, i.e., wild life photo identification have started to offer new ways to monitor animals and to help them to survive.
The goal of the SealVision project is to develop automatic image-based identification of the Saimaa ringed seals.
Thus, each individual seal could be recognized and tracked.
This will further make it possible to make better population size estimates, understand the behaviour of ringed seals, and design more effective measures to protect the population.
The computer vision approach consists of the detection of a seal in game and wild life camera images, the segmentation of the detected seal, and the identification based on ring patterns on the fur.
The research has been supported by Raija ja Ossi Tuuliaisen säätiö.
People
Ekaterina Nepovinnykh
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Office: 2419 |
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Doctoral student |
| Tuomas Eerola
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Office: 2422 |
Tel: +358 40 139 3405 |
Post-Doctoral Researcher |
| Heikki Kälviäinen
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Office: 2415 |
Tel: +358 40 586 7552 |
Professor |
Publications
Identification of Saimaa Ringed Seal Individuals using Transfer Learning
By Ekaterina Nepovinnykh, Tuomas Eerola, and Heikki Kälviäinen,
In the Advanced Concepts for Intelligent Vision Systems (ACIVS 2018), 2018.
Download: PDF DOI
Comparison of Co-segmentation Methods for Wildlife Photo-identification
By Anastasia Popova, Tuomas Eerola, and Heikki Kälviäinen,
In the Advanced Concepts for Intelligent Vision Systems (ACIVS 2018), 2018.
Download: PDF DOI
Saimaa ringed seal fur pattern extraction for identification purposes
By Ekaterina Nepovinnykh,
Master's Thesis, Lappeenranta University of Technology, 2017.
Download: URN
Co-segmentation methods for wildlife-photo identification
By Anastasia Popova,
Master's Thesis, Lappeenranta University of Technology, 2017.
Download: URN
Convolutional neural networks for Saimaa ringed seal segmentation
By Evgeniya Kosyanenko,
Master's Thesis, Lappeenranta University of Technology, 2017.
Download: URN
Automatic individual identification of Saimaa ringed seals
By Tina Chehrsimin, Tuomas Eerola, Meeri Koivuniemi, Miina Auttila, Riikka Levänen, Marja Niemi, Mervi Kunnasranta, and Heikki Kälviäinen,
IET Computer Vision 12 (2), 146 - 152, 2018.
Download: PDF DOI
Enhanced methods for Saimaa ringed seal identification
By Tina Chehrsimin,
Master's Thesis, Lappeenranta University of Technology, 2016.
Download: URN
Segmentation of Saimaa ringed seals for identification purposes
By Artem Zhelezniakov, Tuomas Eerola, Meeri Koivuniemi, Miina Auttila, Riikka Levänen, Marja Niemi, Mervi Kunnasranta, and Heikki Kälviäinen,
In International Symposium on Visual Computing (ISVC 2015), 2015.
Download: PDF DOI
Automatic image-based identification of Saimaa ringed seals
By Artem Zhelezniakov,
Master's Thesis, Lappeenranta University of Technology, 2015.
Download: URN
Links
- Ringed Seal Research, University of Eastern Finland
- Wildlife Photo-ID Network
- Wildbook: Software to Combat Extinction
- I3S: Interactive Individual Identification System
- DISCOVERY: Photo-Identification Data-Management System for Individually Recognizable Animals
- Extract compare, Conservation Research Ltd
- StripeSpotter
- Wild-ID
- Sloop: Pattern Retrieval System for Animal Biometrics