HotSpotter: Using a Computer-Driven Photo-ID Application to Identify Sea Turtles

© 2020 Elsevier B.V. Photo identification (PID) in animal studies has been a widely used method for identifying individuals of many species based on unique natural markings and patterns. The use of PID has facilitated investigations in which residency, home ranges, and growth rates have been assessed. However, many PID studies in the past have relied heavily on manual photo matching. More recently, computer-assisted PID programs have been used to identify individuals of different sea turtle species, and reduced time investment in identifying individuals within specific populations. Still, some computer-based PID programs require significant time investment in ensuring photos are captured at consistent angles and lighting conditions, pre-processing image manipulations, and post-processing manual matching confirmation of potential matches provided by the program. For PID to be an effective time and money saving mechanism for wildlife research and conservation, these common drawbacks need to be addressed with a computer-assisted PID program that reduces manipulation and time investment burden, and consistently provides accurate and reliable results. In this study, we evaluated the accuracy of matching individual face images using the HotSpotter (HS) PID program by building a database of 2136 images of hawksbill (Eretmochelys imbricata) turtles, then querying the database with 158 new images to find matches for individual turtles. Overall, we found that with almost no pre-processing manipulation, and with images from highly variable underwater conditions, qualities, and angles, HS correctly matched individuals in the first choice 80% of the time, increasing to 91% in the first six choices. When assessing in-water images only, accuracy for matching increased from 84% in the first choice, to 94% by the sixth choice. We suggest that the integration of HS technology into a global, web-based PID system will increase the ability to remotely identify individual marine organisms on a global scale, and improve usability for community scientists who may have little to no technical training

Flukebook: an open-source AI platform for cetacean photo identification

Determining which species are at greatest risk, where they are most vulnerable, and what are the trajectories of their communities and populations is critical for conservation and management. Globally distributed, wide-ranging whales and dolphins present a particular challenge in data collection because no single research team can record data over biologically meaningful areas. Flukebook.org is an open-source web platform that addresses these gaps by providing researchers with the latest computational tools. It integrates photo-identification algorithms with data management, sharing, and privacy infrastructure for whale and dolphin research, enabling the global collaborative study of these global species. With seven automatic identification algorithms trained for 15 different species, resulting in 37 species-specific identification pipelines, Flukebook is an extensible foundation that continually incorporates emerging AI techniques and applies them to cetacean photo identification through continued collaboration between computer vision researchers, software engineers, and biologists. With over 2.0 million photos of over 52,000 identified individual animals submitted by over 250 researchers, the platform enables a comprehensive understanding of cetacean populations, fostering international and cross-institutional collaboration while respecting data ownership and privacy. We outline the technology stack and architecture of Flukebook, its performance on real-world cetacean imagery, and its development as an example of scalable, extensible, and reusable open-source conservation software. Flukebook is a step change in our ability to conduct large-scale research on cetaceans across biologically meaningful geographic ranges, to rapidly iterate population assessments and abundance trajectories, and engage the public in actions to protect them.</p

WildMeOrg/houston: Codex 2.1.0

&lt;p&gt;Update major features include Codex ID, change log, sighting flow simplification, search extensions, and accessibility improvements!&lt;/p&gt; &lt;h2&gt;What's Changed&lt;/h2&gt; &lt;ul&gt; &lt;li&gt;AutogeneratedName continued by @naknomum in https://github.com/WildMeOrg/houston/pull/881&lt;/li&gt; &lt;li&gt;additions to ia-config/ files by @naknomum in https://github.com/WildMeOrg/houston/pull/892&lt;/li&gt; &lt;li&gt;Issue 880: individual merge vs AutogeneratedName by @naknomum in https://github.com/WildMeOrg/houston/pull/893&lt;/li&gt; &lt;li&gt;Integrity checks by @naknomum in https://github.com/WildMeOrg/houston/pull/894&lt;/li&gt; &lt;li&gt;882, 883: AutogeneratedName - Sighting/Individual search support by @naknomum in https://github.com/WildMeOrg/houston/pull/895&lt;/li&gt; &lt;li&gt;869, 870: export by @naknomum in https://github.com/WildMeOrg/houston/pull/897&lt;/li&gt; &lt;li&gt;bugfixes related to exporting by @naknomum in https://github.com/WildMeOrg/houston/pull/903&lt;/li&gt; &lt;li&gt;899/900: Sighting search to include Encounter values by @naknomum in https://github.com/WildMeOrg/houston/pull/901&lt;/li&gt; &lt;li&gt;bugfix for customFields in export by @naknomum in https://github.com/WildMeOrg/houston/pull/904&lt;/li&gt; &lt;li&gt;907/908: Individual search results to include most recent sighting fields by @naknomum in https://github.com/WildMeOrg/houston/pull/909&lt;/li&gt; &lt;li&gt;906: deletion of Annotation also removes it from AssetGroupSightings by @naknomum in https://github.com/WildMeOrg/houston/pull/910&lt;/li&gt; &lt;li&gt;911: normalize adoptionName in ElasticSearch by @naknomum in https://github.com/WildMeOrg/houston/pull/912&lt;/li&gt; &lt;li&gt;888: Sighting match_state by @naknomum in https://github.com/WildMeOrg/houston/pull/915&lt;/li&gt; &lt;li&gt;allow admin to delete individuals with public sightings by @naknomum in https://github.com/WildMeOrg/houston/pull/918&lt;/li&gt; &lt;li&gt;566: add numberIndividuals to Sighting search results by @naknomum in https://github.com/WildMeOrg/houston/pull/922&lt;/li&gt; &lt;li&gt;875: ensure that site.species site-settings does not remove in-use taxonomy by @naknomum in https://github.com/WildMeOrg/houston/pull/926&lt;/li&gt; &lt;li&gt;overhaul Sighting.stage usage by @naknomum in https://github.com/WildMeOrg/houston/pull/928&lt;/li&gt; &lt;/ul&gt; &lt;p&gt;&lt;strong&gt;Full Changelog&lt;/strong&gt;: https://github.com/WildMeOrg/houston/compare/v2.0.0...v2.1.0&lt;/p&gt