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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU151167" target="_blank" >RIV/00216305:26220/24:PU151167 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/document/10524098" target="_blank" >https://ieeexplore.ieee.org/document/10524098</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/RADIOELEKTRONIKA61599.2024.10524098" target="_blank" >10.1109/RADIOELEKTRONIKA61599.2024.10524098</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    RADIOELEKTRONIKA 2024: 2024 34th International Conference Radioelektronika

  • ISBN

    979-8-3503-6215-2

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    „“-„“

  • Publisher name

    Institute of Electrical and Electronics Engineers Inc.

  • Place of publication

    neuveden

  • Event location

    Žilina, Slovakia

  • Event date

    Apr 17, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    001229165000040