Paper Info
Title
Place Recognition Using Line-Junction-Lines in Urban Environments
Abstract
Place recognition plays a vital role in eliminating accumulated drift from visual odometry in SLAM system. Bag- of-Words (BoW) -based approach is the most popular solution due to its efficiency and robustness. We propose to use Line- Junction-Line (LJL) to build a BoW for place recognition in urban environments. LJL is a simple structure of two lines with their intersection. Different from point features which are detected based on pixel intensity patterns, it represents structure with physical existence, which is more robust to challenging scenarios. Moreover, its descriptor is distinctive and encodes the relationship between the two lines. Experiments on KITTI dataset show the effectiveness of the proposed method compared to loop detection using BoW trained with either point or line features.
Year
DOI
Venue
2019
10.1109/CIS-RAM47153.2019.9095776
2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM)
Keywords
DocType
ISSN
LJL,BoW,place recognition,Line-Junction-lines,urban environments,KITTI dataset,Bag-of-Words,loop detection,SLAM system
Conference
2326-8123
ISBN
Citations 
PageRank 
978-1-7281-3459-8
0
0.34
References 
Authors
20
7
Name
Order
Citations
PageRank
Xiaoyu Tang101.01
Wenhao Fu200.34
Muyun Jiang300.34
Guohao Peng422.06
Wu Zhenyu513.39
Yufeng Yue614.40
Danwei Wang71529175.13