Computer Science > Computer Vision and Pattern Recognition
[Submitted on 22 Nov 2020 (v1), last revised 19 Jul 2021 (this version, v2)]
Title:CORAL: Colored structural representation for bi-modal place recognition
View PDFAbstract:Place recognition is indispensable for a drift-free localization system. Due to the variations of the environment, place recognition using single-modality has limitations. In this paper, we propose a bi-modal place recognition method, which can extract a compound global descriptor from the two modalities, vision and LiDAR. Specifically, we first build the elevation image generated from 3D points as a structural representation. Then, we derive the correspondences between 3D points and image pixels that are further used in merging the pixel-wise visual features into the elevation map grids. In this way, we fuse the structural features and visual features in the consistent bird-eye view frame, yielding a semantic representation, namely CORAL. And the whole network is called CORAL-VLAD. Comparisons on the Oxford RobotCar show that CORAL-VLAD has superior performance against other state-of-the-art methods. We also demonstrate that our network can be generalized to other scenes and sensor configurations on cross-city datasets.
Submission history
From: Yiyuan Pan [view email][v1] Sun, 22 Nov 2020 04:51:40 UTC (5,553 KB)
[v2] Mon, 19 Jul 2021 11:56:04 UTC (5,927 KB)
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