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

Didier Bieler, Semih Gunel, Pascal Fua, Helge Rhodin; The IEEE International Conference on Computer Vision (ICCV), 2019, pp. 8569-8577

Abstract


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.

Related Material


[pdf]
[bibtex]
@InProceedings{Bieler_2019_ICCV,
author = {Bieler, Didier and Gunel, Semih and Fua, Pascal and Rhodin, Helge},
title = {Gravity as a Reference for Estimating a Person's Height From Video},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}