LiDAR-camera fusion based high-resolution network for efficient road segmentation

Shuhao Huang, Guangming Xiong*, Baochang Zhu, Jianwei Gong, Huiyan Chen

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

This paper addressed the problem of road segmentation using a novel LiDAR-Camera fusion based high-resolution network. Road segmentation in different road conditions has been challenging due to limitations of single sensor. LiDAR could detect height and distance accurately in all road conditions but its data is too sparse for segmenting road, and camera can capture rich visual features but is susceptible to illumination variations and noises. We tackle this problem by fusing the data of these two sensors to complement each other's disadvantages. To achieve better fusion, the LiDAR data is transformed to image-like data and LiDAR features are also transformed adaptively. For better segmentation, we keep high resolution features throughout the convolutional network to reduce information loss and improve segmentation precision. The LiDAR-camera fusion are incorporated into the high-resolution network at multiple layers and multiple scales to constitute our road segmentation system. Comprehensive experiments on KITTI road dataset have been conducted to verify the effectiveness and efficiency of the proposed method.

源语言英语
主期刊名Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020
出版商Institute of Electrical and Electronics Engineers Inc.
830-835
页数6
ISBN(电子版)9781728180250
DOI
出版状态已出版 - 27 11月 2020
活动3rd International Conference on Unmanned Systems, ICUS 2020 - Harbin, 中国
期限: 27 11月 202028 11月 2020

出版系列

姓名Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020

会议

会议3rd International Conference on Unmanned Systems, ICUS 2020
国家/地区中国
Harbin
时期27/11/2028/11/20

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