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Efficient Detection and Tracking of Human Using 3D LiDAR Sensor.

Juan Gómez1, Olivier Aycard1, Junaid Baber1

  • 1Laboratoire d'Informatique (LIG), University of Grenoble Alpes, 38000 Grenoble, France.

Sensors (Basel, Switzerland)
|July 11, 2023
PubMed
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This study introduces a real-time 3D LiDAR system for detecting, tracking, and classifying people. The approach efficiently processes point clouds, achieving high accuracy even in challenging conditions.

Area of Science:

  • Robotics and Computer Vision
  • Sensor Technology
  • Artificial Intelligence

Background:

  • Light Detection and Ranging (LiDAR) is crucial for autonomous systems.
  • 3D point-cloud object detection is vital for real-world applications.
  • Existing methods face challenges in real-time processing and diverse human poses.

Purpose of the Study:

  • To develop a modular, real-time system for person detection, tracking, and classification using 3D LiDAR.
  • To optimize performance on low-power machines by reducing point cloud data.
  • To ensure consistent tracking across various environmental and pose-related challenges.

Main Methods:

  • A modular approach combining object segmentation, geometric descriptor-based classification, and tracking.
Keywords:
3D point cloudclassificationperson detectionreal-timetracking

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  • Real-time processing achieved by predicting regions of interest through movement and motion detection.
  • No prior environmental knowledge is required for operation.

    • Main Results:

    • Successful real-time detection and tracking of persons in indoor 3D LiDAR recordings.
    • Consistent performance despite sensor field-of-view limitations and extreme human poses (crouching, jumping).
    • High confidence in positive human body classifications, outperforming state-of-the-art methods.

    Conclusions:

    • The proposed modular LiDAR system offers a robust and efficient solution for real-time human detection and tracking.
    • The method demonstrates significant potential for applications requiring reliable person identification in complex environments.
    • The system's ability to handle challenging scenarios highlights its practical applicability.