Detail publikace

Dynamic People Counting from Delay-Doppler Images in Challenging Scenarios: Enhancing Model Performance

ALI, M. MARŠÁLEK, R.

Originální název

Dynamic People Counting from Delay-Doppler Images in Challenging Scenarios: Enhancing Model Performance

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This study presents a novel radar-based people counting (PCnt) methodology empowered by deep learning (DL) frameworks. The challenges we face include overfitting due to the model’s tendency to extract highly domain-specific features. These challenges arise from limited data and clutter in indoor settings. To tackle this, our radar system operates in both lab and industrial environments. We propose a 2D-CNN approach and explore ways to handle these challenges, focusing on im proving accuracy through preprocessing techniques. Additionally, we introduced data augmentation strategies to enhance model robustness and mitigate overfitting. Our experiments show our approach accurately counts people moving along the radar line in various environments. However, detecting stationary individuals and distinguishing between moving human and non-human entities remain challenging areas for future work.

Klíčová slova

People counting; heterogeneous clutter environment; preprocessing; data augmentation; deep learning.

Autoři

ALI, M.; MARŠÁLEK, R.

Vydáno

17. 4. 2024

Nakladatel

Institute of Electrical and Electronics Engineers Inc.

ISBN

979-8-3503-6215-2

Kniha

RADIOELEKTRONIKA 2024: 2024 34th International Conference Radioelektronika

Strany počet

6

URL

BibTex

@inproceedings{BUT188392,
  author="Malek {Ali} and Roman {Maršálek}",
  title="Dynamic People Counting from Delay-Doppler Images in Challenging Scenarios: Enhancing Model Performance",
  booktitle="RADIOELEKTRONIKA 2024: 2024 34th International Conference Radioelektronika",
  year="2024",
  pages="6",
  publisher="Institute of Electrical and Electronics Engineers Inc.",
  doi="10.1109/RADIOELEKTRONIKA61599.2024.10524098",
  isbn="979-8-3503-6215-2",
  url="https://ieeexplore.ieee.org/document/10524098"
}