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Announcing DeepPoseKit

We are pleased to announce that the first research paper using Herd Hover data is now available as a preprint on bioArxiv! The paper, titled ‘Fast and robust animal pose estimation,’ presents DeepPoseKit, an open-source software toolkit that allows researchers to extract estimates of animal posture from images or videos. DeepPoseKit is inspired by previous pose-estimation methods, but offers improvements in speed and accuracy, while also emphasizing usability. This work is led by Herd Hover team member Jake Graving and uses our Grevy’s zebra videos as one of the test data sets.

It is particularly exciting that we can now estimate animal postures from drone images. We hope this will open the door to more highly-quantitative field studies of animal behavior and inspire applications for wildlife conservation. We are currently using DeepPoseKit to extract fine-scale behavioral measurements from our drone footage. This allows us to go beyond simply tracking the animals’ positions to really get into the details of individual behaviors and social interactions within our herds.

Jake’s announcement of the preprint on Twitter gained a lot of attention that has already led to some refinements of the manuscript. We are hopeful that a peer-reviewed and published version will be available before long. In the meantime, learn more about the work by reading the preprint. More videos demonstrating the technique are also available on YouTube. The code will be available soon at https://github.com/jgraving/deepposekit.

Preprint citation: Graving JM, Chae D, Naik H, Li L, Koger B, Costelloe BR, Couzin ID. Fast and robust animal pose estimation. bioRxiv 620245. DOI: https://doi.org/10.1101/620245.