Visual Localization in Changing Environments using Place Recognition Techniques | |
Xin, Zhe1,2; Cai, Yinghao1; Cai, Shaojun3; Zhang, Jixiang1; Yang, Yiping1; Wang, Yanqing1 | |
2018 | |
会议名称 | 2018 24th International Conference on Pattern Recognition (ICPR) |
会议日期 | August 20-24, 2018 |
会议地点 | Beijing, China |
摘要 | This paper proposes a visual localization system combining Convolutional Neural Networks (CNNs) and sparse point features to estimate the 6-DOF pose of the robot. The challenges of visual localization across time lie in that the same place captured across time appears dramatically different due to different illumination and weather conditions, viewpoint variations and dynamic objects. In this paper, a novel CNN-based place recognition approach is proposed, which requires no time-consuming feature generation process and no task-specific training. Moreover, we demonstrate that the rich semantic context information obtained from place recognition can greatly improve the subsequent feature matching process for pose estimation. The semantic constraint performs much better than traditional Bag-of-Words based methods for establishing correspondences between the query image and the map. To evaluate the robustness of the algorithm, the proposed system is integrated into ORB-SLAM2 and verified on the data collected over various illumination and weather conditions. Extensive experimental results show that even with weak ORB descriptors, the proposed system can significantly improve the success rate of localization under severe appearance changes. |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39240 |
专题 | 综合信息系统研究中心_视知觉融合及其应用 |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.University of Chinese Academy of Sciences, Beijing, China 3.UISEE Technologies Beijing Co., Ltd |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Xin, Zhe,Cai, Yinghao,Cai, Shaojun,et al. Visual Localization in Changing Environments using Place Recognition Techniques[C],2018. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
08545833.pdf(4950KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论