Multimodal sensor-based semantic 3D mapping for a large-scale environment

作者：

Highlights：

• A novel method to generate semantic 3D map by combining a 3D Lidar and a camera for large-scale environments.

• A refinement method to remove traces of moving vehicles in a 3D map.

• Experiments on challenging sequences and real-world data to compare against state-of-the-art methods.

• Demonstration of superiority in terms of 3D accuracy and intersection over union (IoU).

摘要

•A novel method to generate semantic 3D map by combining a 3D Lidar and a camera for large-scale environments.•A refinement method to remove traces of moving vehicles in a 3D map.•Experiments on challenging sequences and real-world data to compare against state-of-the-art methods.•Demonstration of superiority in terms of 3D accuracy and intersection over union (IoU).

论文关键词：Semantic mapping,Semantic reconstruction,3D mapping,Semantic segmentation,3D refinement

论文评审过程：Received 5 January 2018, Revised 8 March 2018, Accepted 23 March 2018, Available online 27 March 2018, Version of Record 24 April 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.03.051