Comparison of two methods for vehicle extraction from airborne LiDAR data toward motion analysis

Wei Yao, Uwe Stilla

Research output: Journal article publicationJournal articleAcademic researchpeer-review

38 Citations (Scopus)


It has been revealed that single-pass airborne light detection and ranging (LiDAR) system (ALS) data could provide not only the spatial but also the dynamical information of a scanned scene due to the so-called motion artifact effect. A common strategy for extracting dynamical information from ALS data is established based on analyzing shape deformations of vehicles which have to be extracted in advance. Therefore, vehicle extraction results are directly related to the performance of motion analysis. In this letter, two vehicle extraction methods, namely, grid-cell- and 3-D point-cloud-analysis-based methods, which represent two main streams in LiDAR data processing, are to be evaluated and compared toward influences on the performance of motion analysis. Motion estimation based on the two methods is respectively applied to real ALS data sets. The results show that the 3-D data-based method can yield more accurate and robust dynamical traffic information such as motion state and velocity of vehicles, while the grid-cell-based method can provide more complete information by extracting more stationary vehicles.
Original languageEnglish
Article number5692811
Pages (from-to)607-611
Number of pages5
JournalIEEE Geoscience and Remote Sensing Letters
Issue number4
Publication statusPublished - 1 Jul 2011
Externally publishedYes


  • Airborne light detection and ranging (LiDAR)
  • comparative study
  • motion analysis
  • urban traffic
  • vehicle extraction

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Electrical and Electronic Engineering


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