Estimation of physical activities of people in offices from time-series point-cloud data
November 17, 2022 Β· Declared Dead Β· π Consumer Communications and Networking Conference
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Authors
Koki Kizawa, Ryoichi Shinkuma, Gabriele Trovato
arXiv ID
2211.09334
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
Consumer Communications and Networking Conference
Last Checked
5 months ago
Abstract
This paper proposes an edge computing system that enables estimating physical activities of people in offices from time-series point-cloud data, obtained by using a light-detection-and-ranging (LIDAR) sensor network. The paper presents that the proposed system successfully constructs the model for estimating the number of typed characters from time-series point-cloud data, through an experiment using real LIDAR sensors.
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