Primate markerless pose estimation and movement analysis using deeplabcut

Rollyn Labuguen, Dean Karlo Bardeloza, Salvador Blanco Negrete, Jumpei Matsumoto, Kenichi Inoue, Tomohiro Shibata

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Scopus citations

Abstract

The analysis and understanding of primate behavior play a fundamental role in fields such as neuroscience, medicine, psychology, genetics, and more. This paper demonstrates an automatic detection of primate features by using an open-source deep learning toolset, DeepLabCut. We trained the deep neural network to locate 17 features and extract the monkey pose by relating the set of features detected. The model is trained with 5,967 manually annotated monkey images, which achieved train and test set errors of 3.61 and 19.72 unit pixels respectively. We also plotted the feature trajectories across multiple frames to show that the trained model can be used for analyzing behavior.

Original languageEnglish
Title of host publication2019 Joint 8th International Conference on Informatics, Electronics and Vision, ICIEV 2019 and 3rd International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2019 with International Conference on Activity and Behavior Computing, ABC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages297-300
Number of pages4
ISBN (Electronic)9781728107868
DOIs
StatePublished - 2019/05
EventJoint 8th International Conference on Informatics, Electronics and Vision and 3rd International Conference on Imaging, Vision and Pattern Recognition, ICIEV and icIVPR 2019 - Spokane, United States
Duration: 2019/05/302019/06/02

Publication series

Name2019 Joint 8th International Conference on Informatics, Electronics and Vision, ICIEV 2019 and 3rd International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2019 with International Conference on Activity and Behavior Computing, ABC 2019

Conference

ConferenceJoint 8th International Conference on Informatics, Electronics and Vision and 3rd International Conference on Imaging, Vision and Pattern Recognition, ICIEV and icIVPR 2019
Country/TerritoryUnited States
CitySpokane
Period2019/05/302019/06/02

Keywords

  • Deep learning
  • Monkey pose
  • Neural networks

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Signal Processing
  • Instrumentation

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