Articles | Volume 15, issue 1
https://doi.org/10.5194/ms-15-1-2024
https://doi.org/10.5194/ms-15-1-2024
Research article
 | 
03 Jan 2024
Research article |  | 03 Jan 2024

Visual simultaneous localization and mapping (vSLAM) algorithm based on improved Vision Transformer semantic segmentation in dynamic scenes

Mengyuan Chen, Hangrong Guo, Runbang Qian, Guangqiang Gong, and Hao Cheng

Viewed

Total article views: 994 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
662 304 28 994 27 24
  • HTML: 662
  • PDF: 304
  • XML: 28
  • Total: 994
  • BibTeX: 27
  • EndNote: 24
Views and downloads (calculated since 03 Jan 2024)
Cumulative views and downloads (calculated since 03 Jan 2024)

Viewed (geographical distribution)

Total article views: 946 (including HTML, PDF, and XML) Thereof 946 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 17 Nov 2024
Download
Short summary
The proposed VTD-SLAM algorithm has the following advantages. (1) A multiclass feature enhancement and multiclass feature guidance semantic segmentation network (MSNET) is proposed to improve the semantic segmentation ability of dynamic objects. (2) Optimal neighbor pixel matching is used to complete the image of the deleted region. Our method can effectively solve the influence of dynamic objects, so that the SLAM system can operate effectively.