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Vision-Based People Detection System for Heavy Machine Applications.

Vincent Fremont1, Manh Tuan Bui2, Djamal Boukerroui3

  • 1Sorbonne Universités, Université de Technologie de Compiègne, CNRS, UMR 7253, Heudiasyc-CS 60 319, 60 203 Compiègne Cedex, France. vincent.fremont@hds.utc.fr.

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Summary
This summary is machine-generated.

This study introduces a vision-based system using fisheye cameras and LiDAR for enhanced safety in heavy machinery. It effectively reduces false detections and computational costs, improving people detection performance.

Keywords:
deformable part modelfisheye imagesheavy machineshistogram of oriented gradientspedestrian detectionsensor fusion

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Area of Science:

  • Computer Vision
  • Robotics
  • Machine Safety

Background:

  • Heavy machinery operation poses safety risks due to limited visibility.
  • Existing vision-based systems struggle with fisheye lens distortions and computational demands.
  • People detection in fisheye images is an under-researched area.

Purpose of the Study:

  • To develop and evaluate a robust people detection system for heavy machinery safety.
  • To investigate the impact of radial distortions from fisheye cameras on people detection.
  • To integrate LiDAR data to improve detection accuracy and reduce computational load.

Main Methods:

  • A perception system combining a monocular fisheye camera and LiDAR was developed.
  • Approaches for handling fisheye image distortions were adapted and investigated.
  • A sequential LiDAR-based fusion architecture was implemented to enhance the vision-based system.
  • A dedicated heavy machine dataset was created for system evaluation.

Main Results:

  • The proposed system effectively handles radial distortions in fisheye images.
  • LiDAR integration significantly reduces false detections and computational costs.
  • Experimental results demonstrate promising performance in terms of speed and accuracy.
  • The fusion architecture enhances the robustness of the people detection algorithm.

Conclusions:

  • The hybrid vision-LiDAR system offers a viable solution for improving safety in heavy machinery operations.
  • Addressing fisheye distortions and leveraging sensor fusion are key to effective people detection.
  • The developed framework shows potential for real-world deployment in industrial safety applications.