Instance-aware semantic segmentation of road furniture in mobile laser scanning data

F. Li, Zhize Zhou*, Jianhua Xiao, Ruizhi Chen, Matti Lehtomäki, S.J. Oude Elberink, G. Vosselman, Juha Hyyppä, Yuwei Chen, Antero Kukko

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
137 Downloads (Pure)

Abstract

In this paper, we present an improved framework for the instance-aware semantic segmentation of road furniture in mobile laser scanning data. In our framework, we first detect road furniture from mobile laser scanning point clouds. Then we decompose the detected pieces of road furniture into poles and their attached components, and extract the instance information of the components with different features. Most importantly, we classify the components into different categories by combining a classifier and a probabilistic graphic model named DenseCRF, which is the major contribution of this paper. For the classification of the components using DenseCRF, the unary potentials and the pairwise potentials are first obtained. The unary potentials are obtained from the classifier which takes the instance information of components as the input. The pairwise potentials are calculated considering contextual relations between components. By utilising DenseCRF, the contextual consistency of components is preserved, and the performance is significantly improved compared to our previous work. We collect three datasets to test our framework, and compare the classification performances of six different classifiers with and without DenseCRF. The combination of random forest with DenseCRF outperforms the other methods and achieves high overall accuracies of 83.7%, 96.4% and 95.3% in these three datasets. Experimental results demonstrate that our framework reliably assigns both semantic information and instance information for mobile laser scanning point clouds of road furniture.
Original languageEnglish
Pages (from-to)17516-17529
Number of pages14
JournalIEEE transactions on intelligent transportation systems
Volume23
Issue number10
Early online date22 Mar 2022
DOIs
Publication statusPublished - Oct 2022

Keywords

  • 22/1 OA procedure
  • ITC-ISI-JOURNAL-ARTICLE

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