SVG-Loop: Semantic–Visual–Geometric Information-Based Loop Closure Detection

Zhian Yuan, Ke Xu, Xiaoyu Zhou, Bin Deng, Yanxin Ma
2021 Remote Sensing  
Loop closure detection is an important component of visual simultaneous localization and mapping (SLAM). However, most existing loop closure detection methods are vulnerable to complex environments and use limited information from images. As higher-level image information and multi-information fusion can improve the robustness of place recognition, a semantic–visual–geometric information-based loop closure detection algorithm (SVG-Loop) is proposed in this paper. In detail, to reduce the
more » ... rence of dynamic features, a semantic bag-of-words model was firstly constructed by connecting visual features with semantic labels. Secondly, in order to improve detection robustness in different scenes, a semantic landmark vector model was designed by encoding the geometric relationship of the semantic graph. Finally, semantic, visual, and geometric information was integrated by fuse calculation of the two modules. Compared with art-of-the-state methods, experiments on the TUM RBG-D dataset, KITTI odometry dataset, and practical environment show that SVG-Loop has advantages in complex environments with varying light, changeable weather, and dynamic interference.
doi:10.3390/rs13173520 doaj:23de87f2c2584ad0863033039e1af32c fatcat:qcvcljaka5c3flrn6qrzfj32je