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Multiple Monkey Pose Estimation Using OpenPose

Blanco Negrete, S.; Labuguen, R.; Matsumoto, J.; Go, Y.; Inoue, K.-i.; Shibata, T.

2021-01-30 neuroscience
10.1101/2021.01.28.428726 bioRxiv
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This paper proposes a system for pose estimation on monkeys, in diverse and challenging scenarios, and under complex social interactions by using OpenPose. In comparison to most animals used for research, Monkeys present additional difficulties for pose estimation. Multiple degrees of freedom, unique complex postures, intricated social interactions, among others. Our monkey OpenPose trained model is robust against these difficulties. It achieves similar performance as in human pose estimation models, and it can run in Realtime.

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.