Visual Place Recognition of Robots via Global Features of Scan-Context Descriptors with Dictionary-Based Coding
Self-localization is a crucial requirement for visual robot place recognition. Particularly, the 3D point cloud obtained from 3D laser rangefinders (LRF) is applied to it. The critical part is the efficiency and accuracy of place recognition of visual robots based on the 3D point cloud. The current...
Main Authors: | Minying Ye, Kanji Tanaka |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-08-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/15/9040 |
Similar Items
-
MixedSCNet: LiDAR-Based Place Recognition Using Multi-Channel Scan Context Neural Network
by: Yan Si, et al.
Published: (2024-01-01) -
Scene graph descriptors for visual place classification from noisy scene data
by: Tomoya Ohta, et al.
Published: (2023-12-01) -
Deep Localization of Static Scans in Mobile Mapping Point Clouds
by: Yufu Zang, et al.
Published: (2021-01-01) -
Text Spotting towards Perceptually Aliased Urban Place Recognition
by: Dulmini Hettiarachchi, et al.
Published: (2022-11-01) -
LWR-Net: Robust and Lightweight Place Recognition Network for Noisy and Low-Density Point Clouds
by: Zhenghua Zhang, et al.
Published: (2023-10-01)