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Estimating 3D Motion and Forces of Person-Object Interactions from Monocular Video

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F19%3A00337183" target="_blank" >RIV/68407700:21730/19:00337183 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/CVPR.2019.00884" target="_blank" >https://doi.org/10.1109/CVPR.2019.00884</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/CVPR.2019.00884" target="_blank" >10.1109/CVPR.2019.00884</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Estimating 3D Motion and Forces of Person-Object Interactions from Monocular Video

  • Original language description

    In this paper, we introduce a method to automatically reconstruct the 3D motion of a person interacting with an object from a single RGB video. Our method estimates the 3D poses of the person and the object, contact positions, and forces and torques actuated by the human limbs. The main contributions of this work are three-fold. First, we introduce an approach to jointly estimate the motion and the actuation forces of the person on the manipulated object by modelling contacts and the dynamics of their interactions. This is cast as a large-scale trajectory optimization problem. Second, we develop a method to automatically recognize from the input video the position and timing of contacts between the person and the object or the ground, thereby significantly simplifying the complexity of the optimization. Third, we validate our approach on a recent MoCap dataset with ground truth contact forces and demonstrate its performance on a new dataset of Internet videos showing people manipulating a variety of tools in unconstrained environments.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/EF15_003%2F0000468" target="_blank" >EF15_003/0000468: Intelligent Machine Perception</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    CVPR 2019: Proceedings of the 2019 IEEE Conference on Computer Vision and Pattern Recognition

  • ISBN

    978-1-7281-3294-5

  • ISSN

    1063-6919

  • e-ISSN

    2575-7075

  • Number of pages

    10

  • Pages from-to

    8632-8641

  • Publisher name

    IEEE

  • Place of publication

  • Event location

    Long Beach

  • Event date

    Jun 15, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000542649302026