Place Recognition Using Line-Junction-Lines in Urban Environments

• Published in: IEEE ... International Conference on Cybernetics and Intelligent Systems (Print) pp. 530 - 535
• Main Authors: Tang, Xiaoyu, Fu, Wenhao, Jiang, Muyun, Peng, Guohao, Wu, Zhenyu, Yue, Yufeng, Wang, Danwei
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2019
• Subjects: Cameras; Feature extraction; Image segmentation; Robustness; Simultaneous localization and mapping; Visualization
• DOI: 10.1109/CIS-RAM47153.2019.9095776

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.