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LiDAR Filtering in 3D Object Detection Based on Improved RANSAC

Authors :
Bingxu Wang
Jinhui Lan
Jiangjiang Gao
Source :
Remote Sensing; Volume 14; Issue 9; Pages: 2110
Publication Year :
2022
Publisher :
Multidisciplinary Digital Publishing Institute, 2022.

Abstract

At present, the LiDAR ground filtering technology is very mature. There are fewer applications in 3D-object detection due to the limitations of filtering accuracy and efficiency. If the ground can be removed quickly and accurately, the 3D-object detection algorithm can detect objects more accurately and quickly. In order to meet the application requirements of 3D-object detection, inspired by Universal-RANSAC, we analyze the detailed steps of RANSAC and propose a precise and efficient RANSAC-based ground filtering method. The principle of GroupSAC is analyzed, and the sampled points are grouped by attributes to make it easier to sample the correct point. Based on this principle, we devise a method for limiting sampled points that is applicable to point clouds. We describe preemptive RANSAC in detail. Its breadth-first strategy is adopted to obtain the optimal plane without complex iterations. We use the International Society for Photogrammetry and Remote Sensing (ISPRS) datasets and the KITTI dataset for testing. Experiments show that our method has higher filtering accuracy and efficiency compared with the currently widely used methods. We explore the application of ground filtering methods in 3D-object detection, and the experimental results show that our method can improve the object detection accuracy without affecting the efficiency.

Details

Language :
English
ISSN :
20724292
Database :
OpenAIRE
Journal :
Remote Sensing; Volume 14; Issue 9; Pages: 2110
Accession number :
edsair.doi.dedup.....50f8cc6378494e7f28ba57d0a7a52b47
Full Text :
https://doi.org/10.3390/rs14092110