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  4. Gravity as a Reference for Estimating a Person's Height from Video
 
conference paper

Gravity as a Reference for Estimating a Person's Height from Video

Bieler, Didier
•
Gunel, Semih  
•
Fua, Pascal  
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January 1, 2019
2019 Ieee/Cvf International Conference On Computer Vision (Iccv 2019)
IEEE/CVF International Conference on Computer Vision (ICCV)

Estimating the metric height of a person from monocular imagery without additional assumptions is ill-posed. Existing solutions either require manual calibration of ground plane and camera geometry, special cameras, or reference objects of known size. We focus on motion cues and exploit gravity on earth as an omnipresent reference 'object' to translate acceleration, and subsequently height, measured in image-pixels to values in meters. We require videos of motion as input, where gravity is the only external force. This limitation is different to those of existing solutions that recover a person's height and, therefore, our method opens up new application fields. We show theoretically and empirically that a simple motion trajectory analysis suffices to translate from pixel measurements to the person's metric height, reaching a MAE of up to 3.9 cm on jumping motions, and that this works without camera and ground plane calibration.

  • Details
  • Metrics
Type
conference paper
DOI
10.1109/ICCV.2019.00866
Web of Science ID

WOS:000548549203069

Author(s)
Bieler, Didier
Gunel, Semih  
Fua, Pascal  
Rhodin, Helge  
Date Issued

2019-01-01

Publisher

IEEE

Publisher place

New York

Published in
2019 Ieee/Cvf International Conference On Computer Vision (Iccv 2019)
ISBN of the book

978-1-7281-4803-8

Series title/Series vol.

IEEE International Conference on Computer Vision

Start page

8568

End page

8576

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CVLAB  
Event nameEvent placeEvent date
IEEE/CVF International Conference on Computer Vision (ICCV)

Seoul, SOUTH KOREA

Oct 27-Nov 02, 2019

Available on Infoscience
August 6, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/170642
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