Positional accuracy analysis of YOLO personal mobility detection

Junseok Kim, Taehyun Lee, Youkyung Han, Junho Yeom

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

Abstract

As personal mobility (PM) becomes increasingly prevalent in urban environments, the precise detection and monitoring of PM is crucial for urban aesthetics and safety. Therefore, in this study, the YOLO algorithm, renowned for its efficiency and effectiveness in object detection tasks, is employed to detect PM from UAV orthophotos. Additionally, the positional accuracy of the detected PM is evaluated using ground-truth data. Given that PM is relatively small compared to other urban objects, the feasibility of detecting and precisely locating PM was analyzed. The assumption that the centroid of the bounding boxes detected by the YOLO algorithm adequately represents the position of the detected objects was also verified. Aerial photos were collected at a 50 m altitude with an RTK UAV over three study sites. Each site contains approximately 15 PM, and their centroid coordinates were investigated through VRS GNSS surveying. For accurate geo-rectification of raw UAV images, five ground control points were installed on each site, and their coordinates were surveyed. The PM detection results showed that the positional accuracy of the PM centers had an error of 13.95 cm. Finally, it was confirmed that UAV photogrammetry and machine learning applications are effective methods for the precise detection and monitoring of PM in urban environments.

Original languageEnglish
Title of host publicationRemote Sensing Technologies and Applications in Urban Environments IX
EditorsThilo Erbertseder, Nektarios Chrysoulakis, Ying Zhang
PublisherSPIE
ISBN (Electronic)9781510681040
DOIs
StatePublished - 2024
EventRemote Sensing Technologies and Applications in Urban Environments IX 2024 - Edinburgh, United Kingdom
Duration: 16 Sep 2024 → …

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume13198
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceRemote Sensing Technologies and Applications in Urban Environments IX 2024
Country/TerritoryUnited Kingdom
CityEdinburgh
Period16/09/24 → …

Keywords

  • UAV
  • YOLO
  • object detection
  • personal mobility
  • positional accuracy

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