Enhanced Speed Estimation Based on 2D Object Detection and Monocular Vehicle Pose Estimation

Shao Ru Wang*, Chen Chien Hsu, Cheng Wei Peng, Cheng Kai Lu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study aims to enhance the accuracy of vehicle speed estimation in camera-based Intelligent Transportation Systems (ITS). By integrating advanced technologies, including YOLOv7 object detection, ByteTrack multi-object tracking, and Ego-Net monocular vehicle pose estimation, we have improved the reliability of speed estimation results. Experimental findings demonstrate that our novel framework significantly increases the accuracy of estimation, providing trustworthy speed estimation results. The study validates the feasibility of this framework, offering experimental results highly consistent with ground truth GPS data and providing robust support for ITS research and applications.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Consumer Electronics, ICCE 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350324136
DOIs
Publication statusPublished - 2024
Event2024 IEEE International Conference on Consumer Electronics, ICCE 2024 - Las Vegas, United States
Duration: 2024 Jan 62024 Jan 8

Publication series

NameDigest of Technical Papers - IEEE International Conference on Consumer Electronics
ISSN (Print)0747-668X
ISSN (Electronic)2159-1423

Conference

Conference2024 IEEE International Conference on Consumer Electronics, ICCE 2024
Country/TerritoryUnited States
CityLas Vegas
Period2024/01/062024/01/08

Keywords

  • 2D Object Detection
  • ITS
  • Multiple Object Tracking
  • Vehicle pose Estimation

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering

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