Continuous People Crowd Monitoring defined as a Regression Problem using Radar Networks

Continuous People Crowd Monitoring defined as a Regression Problem using Radar Networks

Guendel, Ronny (TU Delft Microwave Sensing, Signals & Systems)
Ullmann, I. (Friedrich-Alexander-Universität Erlangen-Nürnberg)
Fioranelli, F. (TU Delft Microwave Sensing, Signals & Systems)
Yarovoy, Alexander (TU Delft Microwave Sensing, Signals & Systems)

2023

Radar-based human activity recognition in crowded environments using regression approaches is addressed. Whereas previous research has focused on single activities and subjects, the problem of continuous activity recognition involving up to five individuals moving in arbitrary directions in an indoor area is introduced. To treat the problem, a regression-based approach is used, which offers innovative insights into creating robust and accurate systems for monitoring human activities.Novel approaches utilizing LSTM or CNN regression techniques with Linear Regression and Support Vector Machine regressor are compared on extracted features from radar data through the Histogram of Oriented Gradients and Principal Component Analysis. These approaches are rigorously evaluated by a Leave-One-Group-Out method, with performance assessed using common regression metrics such as the RMSE. The most promising outcomes were observed for crowds of three and five individuals, with respective RMSE of approximately 0.4 and 0.6. These results were primarily achieved by utilizing the micro-Doppler (µD) Spectrogram or range-Doppler data domain.

Radar Signal Processing
Multiple People Monitoring
Distributed Radar
Machine Learning
Deep Learning
Histogram of Oriented Gradients
Principal Component Analysis
Regression
LSTM
CNN

http://resolver.tudelft.nl/uuid:4de2466a-f615-47d2-a263-420d78e490ab

https://doi.org/10.23919/EuRAD58043.2023.10289622

IEEE

2024-04-26

979-8-3503-2246-0

Proceedings of the 2023 20th European Radar Conference (EuRAD)

2023 20th European Radar Conference (EuRAD), 2023-09-20 → 2023-09-22, Berlin, Germany

20th European Radar Conference, EuRAD 2023

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

conference paper

© 2023 Ronny Guendel, I. Ullmann, F. Fioranelli, Alexander Yarovoy