id |
caadria2022_297 |
authors |
Zhou, Margaret Z., Chen, Shi Yu and Garcia del Castillo y Lopez, Jose Luis |
year |
2022 |
title |
Elemental Motion in Spatial Interaction (EMSI): A Framework for Understanding Space through Movement and Computer Vision |
doi |
https://doi.org/10.52842/conf.caadria.2022.1.505
|
source |
Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 505-514 |
summary |
Spatial analysis and evaluation are becoming increasingly common as new technologies enable users, designers, and researchers to study spatial motion patterns without relying on manual notations for observations. While ideas related to motion and space have been studied in other fields such as industrial engineering, choreography, and computer science, the understanding of efficiency and quality in architectural spaces through motion has not been widely explored. This research applies techniques in computer vision to analyse human body motion in architectural spaces as a measure of experience and engagement. A taxonomy framework is proposed to categorize human motion components relevant to spatial interactions, for analysis through computer vision. A technical case study developed upon a machine-learning-aided model is used to test a selection of the proposed framework within domestic kitchen environments. This contribution adds further perspective to wider research explorations in the quality, inclusivity, engagement, and efficiency of architectural spaces through computer-aided tools. |
keywords |
Pose Estimation, Spatial Evaluation, Architectural Usability, Motion Studies, Computer Vision, SDG 3, SDG 9 |
series |
CAADRIA |
email |
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full text |
file.pdf (616,496 bytes) |
references |
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last changed |
2022/07/22 07:34 |
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