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Estimating 3D Motion and Forces of Human–Object Interactions from Internet Videos

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F22%3A00356153" target="_blank" >RIV/68407700:21730/22:00356153 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1007/s11263-021-01540-1" target="_blank" >https://doi.org/10.1007/s11263-021-01540-1</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/s11263-021-01540-1" target="_blank" >10.1007/s11263-021-01540-1</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Estimating 3D Motion and Forces of Human–Object Interactions from Internet Videos

  • 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 together with the object pose, the contact positions and the contact forces exerted on the human body. 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 modeling contacts and the dynamics of the interactions. This is cast as a large-scale trajectory optimization problem. Second, we develop a method to automatically recognize from the input video the 2D 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 video + MoCap dataset capturing typical parkour actions, 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

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • 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

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    International Journal of Computer Vision

  • ISSN

    0920-5691

  • e-ISSN

    1573-1405

  • Volume of the periodical

    130

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    21

  • Pages from-to

    363-383

  • UT code for WoS article

    000738560100004

  • EID of the result in the Scopus database

    2-s2.0-85122284235