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    ZooBuilder: 2D and 3D Pose Estimation for Quadrupeds Using Synthetic Data

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    Date
    2020
    Author
    Fangbemi, Abassin Sourou
    Lu, Yi Fei
    Xu, Maoyuan
    Luo, Xiaowu
    Rolland, Alexis
    Raissi, Chedy
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    Abstract
    This work introduces a novel strategy for generating synthetic training data for 2D and 3D pose estimation of animals using keyframe animations. With the objective to automate the process of creating animations for wildlife, we train several 2D and 3D pose estimation models with synthetic data, and put in place an end-to-end pipeline called ZooBuilder. The pipeline takes as input a video of an animal in the wild, and generates the corresponding 2D and 3D coordinates for each joint of the animal's skeleton. With this approach, we produce motion capture data that can be used to create animations for wildlife.
    BibTeX
    @inproceedings {10.2312:sca.20201217,
    booktitle = {Eurographics/ ACM SIGGRAPH Symposium on Computer Animation - Showcases},
    editor = {Holden, Daniel},
    title = {{ZooBuilder: 2D and 3D Pose Estimation for Quadrupeds Using Synthetic Data}},
    author = {Fangbemi, Abassin Sourou and Lu, Yi Fei and Xu, Maoyuan and Luo, Xiaowu and Rolland, Alexis and Raissi, Chedy},
    year = {2020},
    publisher = {The Eurographics Association},
    ISSN = {1727-5288},
    ISBN = {978-3-03868-129-8},
    DOI = {10.2312/sca.20201217}
    }
    URI
    https://doi.org/10.2312/sca.20201217
    https://diglib.eg.org:443/handle/10.2312/sca20201217
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA