Raw images, annotations, and vvipr code archive to support 'Evaluating thermal and color sensors for automating detection of penguins and pinnipeds in images collected with an unoccupied aerial system''

• Main Authors: Hinke, Jefferson T., Giuseffi, Louise M., Hermanson, Victoria R., Woodman, Samuel M., Krause, Douglas J.
• Format: Other/Unknown Material
• Language: English
• Published: Zenodo 2022
• Subjects: VIAME; machine learning; image analysis; Antarctica; drone; shiny; R; penguin; fur seal; Antarc*; Antarctic; Antarctic Fur Seals; antarcticus; Arctocephalus gazella; Livingston Island; Pygoscelis papua
• Online Access: https://doi.org/10.5281/zenodo.6714100

Images, annotations,and code archived here were used in the paper "Evaluating a machine learning approach to detect penguins and pinnipeds in thermal and color images collected with an unoccupied aerial system" submitted for publication in Drones. The filescontain raw thermal and color images of aggregations of gentoo ( Pygoscelis papua ) and chinstrap ( P. antarcticus ) penguins and Antarctic fur seals ( Arctocephalus gazella ). All images were collected with the Flir DuoPro R camera (Teledyne FLIR LLC, Wilsonville, OR, U.S.A.), carried into flight under an APH-28 hexacopter (Aerial Imaging Solutions, LLC, Old Lyme, CT, U . S . A .) at Cape Shirreff, Livingston Island, Antarctica (60.79 °W, 62.46 °S), during the austral summer of 2019-20. All aerial surveys occurred under the Marine Mammal Protection Act Permit No. 20599 granted by the Office of Protected Resources/National Marine Fisheries Service, the Antarctic Conservation Act Permit No. 2017-012, NMFS-SWFSC Institutional Animal Care and Use Committee Permit No. SWPI 2014-03R, and all domestic and international UAS flight regulations. The annotations of the images were conducted using VIAME desktop software (v 0.16.1 or later; https://github.com/VIAME ) or the online using the DIVE interface (https://viame.kitware.com/). Model results were assessed with the vvipr code (v.0.3.2), archived hereand available online (https://github.com/us-amlr/vvipr/releases/tag/v0.3.2).