A Graph-Matching Approach for Cross-view Registration of Over-view 2 and Street-view based Point Clouds

• URL: http://arxiv.org/abs/2202.06857v1
• Date: Mon, 14 Feb 2022 16:43:28 GMT
• Title: A Graph-Matching Approach for Cross-view Registration of Over-view 2 and Street-view based Point Clouds
• Authors: Xiao Ling, Rongjun Qin
• Abstract summary: We propose a fully automated geo-registration method for cross-view data, which utilizes semantically segmented object boundaries as view-invariant features. The proposed method models segments of buildings as nodes of graphs, both detected from the satellite-based and street-view based point clouds. The matched nodes will be subject to a further optimization to allow precise-registration, followed by a constrained bundle adjustment on the street-view image to keep 2D29 3D consistencies.
• Score: 4.742825811314168
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In this paper, based on the assumption that the object boundaries (e.g., buildings) from the over-view data should coincide with footprints of fa\c{c}ade 3D points generated from street-view photogrammetric images, we aim to address this problem by proposing a fully automated geo-registration method for cross-view data, which utilizes semantically segmented object boundaries as view-invariant features under a global optimization framework through graph-matching: taking the over-view point clouds generated from stereo/multi-stereo satellite images and the street-view point clouds generated from monocular video images as the inputs, the proposed method models segments of buildings as nodes of graphs, both detected from the satellite-based and street-view based point clouds, thus to form the registration as a graph-matching problem to allow non-rigid matches; to enable a robust solution and fully utilize the topological relations between these segments, we propose to address the graph-matching problem on its conjugate graph solved through a belief-propagation algorithm. The matched nodes will be subject to a further optimization to allow precise-registration, followed by a constrained bundle adjustment on the street-view image to keep 2D29 3D consistencies, which yields well-registered street-view images and point clouds to the satellite point clouds.

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