Automated algorithm for removing clutter objects in mms point cloud for 3D road mapping

Jisang Lee, Suhong Yoo, Seunghwan Hong, Mohammad Gholami Farkoushi, Junsu Bae, Ilsuk Park, Hong Gyoo Sohn

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Road information high definition maps (HD map) contain information about the facilities around the roads and are often constructed through a mobile mapping system (MMS). Although constructing an HD map is essential for road maintenance and the application of autonomous driving in the future, it is problematic to acquire the data of objects other than the facilities in an unstructured form while operating the MMS. In this study, the researchers define this object data as clutter objects and present a method of automatic removal using characteristics of the MMS and image segmentation techniques. By applying the method to 10 KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago) datasets, clutter objects were removed with an average overall accuracy of 91% with 0% (0.448%) error of commission for the complete point cloud map.

Original languageEnglish
Article number4076
Pages (from-to)1-11
Number of pages11
JournalSensors (Switzerland)
Issue number15
Publication statusPublished - 2020 Aug 1

Bibliographical note

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering


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