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Research on Multi-View 3D Reconstruction Technology Based on SFM
| Content Provider | MDPI |
|---|---|
| Author | Gao, Lei Zhao, Yingbao Han, Jingchang Liu, Huixian |
| Copyright Year | 2022 |
| Description | Multi-view 3D reconstruction technology is used to restore a 3D model of practical value or required objects from a group of images. This paper designs and implements a set of multi-view 3D reconstruction technology, adopts the fusion method of SIFT and SURF feature-point extraction results, increases the number of feature points, adds proportional constraints to improve the robustness of feature-point matching, and uses RANSAC to eliminate false matching. In the sparse reconstruction stage, the traditional incremental SFM algorithm takes a long time, but the accuracy is high; the traditional global SFM algorithm is fast, but its accuracy is low; aiming at the disadvantages of traditional SFM algorithm, this paper proposes a hybrid SFM algorithm, which avoids the problem of the long time consumption of incremental SFM and the problem of the low precision and poor robustness of global SFM; finally, the MVS algorithm of depth-map fusion is used to complete the dense reconstruction of objects, and the related algorithms are used to complete the surface reconstruction, which makes the reconstruction model more realistic. |
| Starting Page | 4366 |
| e-ISSN | 14248220 |
| DOI | 10.3390/s22124366 |
| Journal | Sensors |
| Issue Number | 12 |
| Volume Number | 22 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2022-06-09 |
| Access Restriction | Open |
| Subject Keyword | Sensors Industrial Engineering Multi-view 3d Reconstruction Feature-point Detection and Matching Sparse Reconstruction a Dense Reconstruction |
| Content Type | Text |
| Resource Type | Article |
