TY - GEN
T1 - Place Recognition Using Line-Junction-Lines in Urban Environments
AU - Tang, Xiaoyu
AU - Fu, Wenhao
AU - Jiang, Muyun
AU - Peng, Guohao
AU - Wu, Zhenyu
AU - Yue, Yufeng
AU - Wang, Danwei
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85085864128&partnerID=8YFLogxK
U2 - 10.1109/CIS-RAM47153.2019.9095776
DO - 10.1109/CIS-RAM47153.2019.9095776
M3 - Conference contribution
AN - SCOPUS:85085864128
T3 - Proceedings of the IEEE 2019 9th International Conference on Cybernetics and Intelligent Systems and Robotics, Automation and Mechatronics, CIS and RAM 2019
SP - 530
EP - 535
BT - Proceedings of the IEEE 2019 9th International Conference on Cybernetics and Intelligent Systems and Robotics, Automation and Mechatronics, CIS and RAM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th IEEE International Conference on Cybernetics and Intelligent Systems and Robotics, Automation and Mechatronics, CIS and RAM 2019
Y2 - 18 November 2019 through 20 November 2019
ER -