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Lion preservation with computer vision
A computer vision approach proved to be successful in animal tracking.
Helping wild animals conservation with machine learning.
The Lion Identification Network of Collaborators - LINC - monitors lions to help with their preservation across African territory. This community of conservationists and researchers in conjunction with IEF R&D created an open-source platform to track Panthera Leo in order to maintain the genetic viability of the species and create better policy decisions to protect the last remaining lions.
Challenge
Conservationists needed to automate the process of identification of over 400 lions. To accurately monitor the population and better understand the connectivity between them, researchers in the past used to manually track lion's movements by comparing hundreds of pictures or utilizing GPS collars.
Solution
A computer vision system with a pattern recognition software now serves as an automated, non-invasive solution for identifying and monitoring lions. By recognizing face and whisker patterns in lion images conservationists can collectively locate the animals by sharing their images information in a system that classifies and identifies the population.
Discover our approach
Develop a computer vision automated solution and pattern recognition software in 3 stages:
Lion feature object detection
Using a dataset of lion images that are tagged with bounding boxes around features, such as head, eyes and nose, the algorithm identifies the feature classes in new photos.
It has been a great working experience and our team looks forward to working with Tryolabs in the future on this unique conservation challenge.
Interested in object detection?
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