Lu, X.; Wang, H.; Tang, S.; Huang, H.; Li, C. DM-SLAM: Monocular SLAM in Dynamic Environments. Preprints2020, 2020010123. https://doi.org/10.20944/preprints202001.0123.v1
APA Style
Lu, X., Wang, H., Tang, S., Huang, H., & Li, C. (2020). DM-SLAM: Monocular SLAM in Dynamic Environments. Preprints. https://doi.org/10.20944/preprints202001.0123.v1
Chicago/Turabian Style
Lu, X., Huimin Huang and Chuang Li. 2020 "DM-SLAM: Monocular SLAM in Dynamic Environments" Preprints. https://doi.org/10.20944/preprints202001.0123.v1
Abstract
Many classic visual monocular SLAM systems have been developed over the past decades, however, most of them will fail when dynamic scenarios dominate. DM-SLAM is proposed for handling dynamic objects in environments based on ORB-SLAM. The article mainly concentrates on two aspects. Firstly, DLRSAC is proposed to extract static features from the dynamic scene based on awareness of nature difference between motion and static, which is integrated into initialization of DM-SLAM. Secondly, we design candidate map points selection mechanism based on neighborhood mutual exclusion to balance the accuracy of tracking camera pose and system robustness in motion scenes. Finally, we conduct experiments in the public dataset and compare DM-SLAM with ORB-SLAM. The experiments verify the superiority of the DM-SLAM.
Keywords
static features extraction; dynamic environments; 3D reconstruction; monocular SLAM
Subject
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
