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Automatic Traffic Camera Calibration Using 3D Scene Reconstruction with Structure-from-Motion and Custom Image Data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0198171" target="_blank" >RIV/00216305:26220/26:0198171 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Automatic Traffic Camera Calibration Using 3D Scene Reconstruction with Structure-from-Motion and Custom Image Data

  • Original language description

    Traffic cameras play a crucial role in monitoring and managing transportation systems, and accurate calibration is essential for reliable data acquisition. Traditional calibration methods often require manual interventions, physical markers, or specific tools, which can be both time-consuming and costly, especially in complex urban environments. To overcome these challenges, recent methods use the 3D reconstruction of the scene using the Structure-from-Motion (SfM) techniques. This allows for a precise traffic camera localization in the model and then finding the intrinsic and extrinsic camera parameters. However, these methods typically rely on high-quality image data from public sources such as Google Streeve View (GSV), which does not always provide images that are up to date or sometimes are not available for a given location. In this paper, we introduce a new approach of automatic camera calibration via the SfM techniques using our own data. Testing was conducted using a custom dataset consisting of images taken from various angles, followed by the 3D reconstruction and calibration process. We evaluated our approach on the task of distance measurements in the view of the traffic camera. The results demonstrate an accuracy of measurements with an error margin of 1.03 meter, showcasing the effectiveness of the proposed method in real world applications.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

    <a href="/en/project/CK04000027" target="_blank" >CK04000027: Traffic controll system of new generation (SENDER)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    ICUMT 2024; 16th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops

  • ISBN

    978-3-8007-6544-7

  • ISSN

  • e-ISSN

    2157-023X

  • Number of pages

    6

  • Pages from-to

    19-24

  • Publisher name

  • Place of publication

  • Event location

    Meloneras, Gran Canaria, Spain

  • Event date

    Nov 26, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article