Laser & Optoelectronics Progress, Volume. 61, Issue 4, 0437003(2024)
Visual SLAM Algorithm Based on Weighted Static in Dynamic Environment
Fig. 3. Two Ghost modules. (a) DFC attention; (b) GhostNetV2Bottleneck module; (c) GhostV2C3 module
Fig. 4. Schematic of the epipolar constraint. (a) Case of meeting the epipolar constraint; (b) case where the epipolar constraint is not met
Fig. 5. Removing dynamic feature points. (a) Semantic segmentation; (b) semantic segmentation removal; (c) pole constraint removal; (d) weighted geometric constraint removal
Fig. 6. Absolute trajectory error map, 3D trajectory error heat map, and relative pose error map. (a) fr3/walking_xyz sequence; (b) fr3/walking_rpt sequence; (c) fr3/sitting_static sequence
Fig. 7. Experiments using RGB-D cameras in a real dynamic scene. (a) Experiment scene; (b) experimental result
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Yong Li, Haibo Wu, Wan Li, Dongze Li. Visual SLAM Algorithm Based on Weighted Static in Dynamic Environment[J]. Laser & Optoelectronics Progress, 2024, 61(4): 0437003
Category: Digital Image Processing
Received: May. 8, 2023
Accepted: Jul. 24, 2023
Published Online: Feb. 26, 2024
The Author Email: Haibo Wu (whb_kust@kust.edu.cn)
CSTR:32186.14.LOP231254