Aerial LiDAR-based 3D Object Detection and Tracking for Traffic Monitoring

Baya Cherif, Hakim Ghazzai, Ahmad Alsharoa, Hichem Besbes, Yehia Massoud

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The proliferation of Light Detection and Ranging (LiDAR) technology in the automotive industry has quickly promoted its use in many emerging areas in smart cities and internet-of-things. Compared to other sensors, like cameras and radars, LiDAR provides up to 64 scanning channels, vertical and horizontal field of view, high precision, high detection range, and great performance under poor weather conditions. In this paper, we propose a novel aerial traffic monitoring solution based on Light Detection and Ranging (LiDAR) technology. By equipping unmanned aerial vehicles (UAVs) with a LiDAR sensor, we generate 3D point cloud data that can be used for object detection and tracking. Due to the unavailability of LiDAR data from the sky, we propose to use a 3D simulator. Then, we implement PointVoxel-RCNN (PV-RCNN) to perform road user detection (e.g., vehicles and pedestrians). Subsequently, we implement an Unscented Kalman filter, which takes a 3D detected object as input and uses its information to predict the state of the 3D box before the next LiDAR scan gets loaded. Finally, we update the measurement by using the new observation of the point cloud and correct the previous prediction's belief. The simulation results illustrate the performance gain (around 8 %) achieved by our solution compared to other 3D point cloud solutions.

Original languageEnglish (US)
Title of host publicationISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665451093
DOIs
StatePublished - 2023
Event56th IEEE International Symposium on Circuits and Systems, ISCAS 2023 - Monterey, United States
Duration: May 21 2023May 25 2023

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2023-May
ISSN (Print)0271-4310

Conference

Conference56th IEEE International Symposium on Circuits and Systems, ISCAS 2023
Country/TerritoryUnited States
CityMonterey
Period05/21/2305/25/23

Keywords

  • deep learning
  • detection
  • LiDAR
  • tracking
  • Traffic monitoring
  • UAV

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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