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Pure Vision-Based Motion Tracking for Data-Driven Design – A Simple, Flexible, and Cost-Effective Approach for Capturing Static and Dynamic Interactions

Published online by Cambridge University Press:  26 May 2022

S. H. Johnston ,
M. F. Berg ,
S. W. Eikevåg ,
D. N. Ege ,
S. Kohtala  and
M. Steinert
S. H. Johnston*
Affiliation:
Norwegian University of Science and Technology, Norway
M. F. Berg
Affiliation:
Norwegian University of Science and Technology, Norway
S. W. Eikevåg
Affiliation:
Norwegian University of Science and Technology, Norway
D. N. Ege
Affiliation:
Norwegian University of Science and Technology, Norway
S. Kohtala
Affiliation:
Norwegian University of Science and Technology, Norway
M. Steinert
Affiliation:
Norwegian University of Science and Technology, Norway
*
Sondrhjo@stud.ntnu.no

Abstract

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This paper presents an exploratory case study where video-based pose estimation is used to analyse human motion to support data-driven design. It provides two example use cases related to design. Results are compared to ground truth measurements showing high correlation for the estimated pose, with an RMSE of 65.5 mm. The paper exemplifies how design projects can benefit from a simple, flexible, and cost-effective approach to capture human-object interactions. This also entails the possibility of implementing interaction and body capturing in the earliest stages of design, at minimal effort.

Keywords

design methodsinteraction designvision-based body-trackingdata-driven design

Information

Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 485 - 494
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

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