DP-MVS: Detail Preserving Multi-View Surface Reconstruction of Large-Scale Scenes

This paper presents an accurate and robust dense 3D reconstruction system for detail preserving surface modeling of large-scale scenes from multi-view images, which we named DP-MVS. Our system performs high-quality large-scale dense reconstruction, which preserves geometric details for thin structur...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2021-11, Vol.13 (22), p.4569
Main Authors: Zhou, Liyang, Zhang, Zhuang, Jiang, Hanqing, Sun, Han, Bao, Hujun, Zhang, Guofeng
Format: Article
Language:English
Subjects:
Accuracy
Computer graphics
depth estimation
detail preserving
Digital cameras
Digital imaging
Finite element method
Image reconstruction
Methods
multi-view reconstruction
Optimization
Run time (computers)
surface meshing
Unmanned aerial vehicles
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Summary:This paper presents an accurate and robust dense 3D reconstruction system for detail preserving surface modeling of large-scale scenes from multi-view images, which we named DP-MVS. Our system performs high-quality large-scale dense reconstruction, which preserves geometric details for thin structures, especially for linear objects. Our framework begins with a sparse reconstruction carried out by an incremental Structure-from-Motion. Based on the reconstructed sparse map, a novel detail preserving PatchMatch approach is applied for depth estimation of each image view. The estimated depth maps of multiple views are then fused to a dense point cloud in a memory-efficient way, followed by a detail-aware surface meshing method to extract the final surface mesh of the captured scene. Experiments on ETH3D benchmark show that the proposed method outperforms other state-of-the-art methods on F1-score, with the running time more than 4 times faster. More experiments on large-scale photo collections demonstrate the effectiveness of the proposed framework for large-scale scene reconstruction in terms of accuracy, completeness, memory saving, and time efficiency.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs13224569