Single Image Human Proxemics Estimation for Visual Social Distancing
IEEE Winter Conference on Applications of Computer Vision (WACV)
; : 2784-2794, 2021.
Article
in English
| Web of Science | ID: covidwho-1432225
ABSTRACT
In this work, we address the problem of estimating the so-called "Social Distancing" given a single uncalibrated image in unconstrained scenarios. Our approach proposes a semi-automatic solution to approximate the homography matrix between the scene ground and image plane. With the estimated homography, we then leverage an off-the-shelf pose detector to detect body poses on the image and to reason upon their inter-personal distances using the length of their body-parts. Inter-personal distances are further locally inspected to detect possible violations of the social distancing rules. We validate our proposed method quantitatively and qualitatively against baselines on public domain datasets for which we provided groundtruth on interpersonal distances. Besides, we demonstrate the application of our method deployed in a real testing scenario where statistics on the inter-personal distances are currently used to improve the safety in a critical environment.
Full text:
Available
Collection:
Databases of international organizations
Database:
Web of Science
Language:
English
Journal:
IEEE Winter Conference on Applications of Computer Vision (WACV)
Year:
2021
Document Type:
Article
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