3D Reconstruction through Fusion of Cross-View Images
Not on the map. Why?
Abstract (arXiv)
3D recovery from multi-stereo and stereo images, as an important application of the image-based perspective geometry, serves many applications in computer vision, remote sensing and Geomatics. In this chapter, the authors utilize the imaging geometry and present approaches that perform 3D reconstruction from cross-view images that are drastically different in their viewpoints. We introduce our framework that takes ground-view images and satellite images for full 3D recovery, which includes necessary methods in satellite and ground-based point cloud generation from images, 3D data co-registration, fusion and mesh generation. We demonstrate our proposed framework on a dataset consisting of twelve satellite images and 150k video frames acquired through a vehicle-mounted Go-pro camera and demonstrate the reconstruction results. We have also compared our results with results generated from an intuitive processing pipeline that involves typical geo-registration and meshing methods.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 5 of its 58 references that are in the map. First posted on arXiv 27 Jun 2021.
Builds on
5 of 58 references.
References · 5
- 2016ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Camerascited by 806
- 2017Cross-View Image Matching for Geo-localization in Urban Environmentscited by 69
- 2018Cross-View Image Synthesis using Conditional GANscited by 69
- 2015Semantic Cross-View Matchingcited by 31
- 2019Automated 3D recovery from very high resolution multi-view satellite imagescited by 6
Built on by
Citing papers per year: 2025: 2.
2 papers.