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.
Bibliographical noteFunding Information:
Acknowledgments: This research was supported by a grant from the Water Management Research Program funded by the Ministry of Land, Infrastructure and Transport of the Korean government (20AWMP-B121100-05). We would like to thank Editage (www.editage.co.kr) for English language editing.
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
All Science Journal Classification (ASJC) codes
- Analytical Chemistry
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering