Comparison of 3D Reconstruction between Neural Radiance Fields and Structure-from-Motion-Based Photogrammetry from 360° Videos
Publication: Computing in Civil Engineering 2023
ABSTRACT
Imagery is a standard modality of visual data capture on construction sites for documenting construction progress. Assimilating the data from multiple disjointed 2D images into a single 3D format enhances visualization and scene understanding and increases the data usability for tasks like quantity estimation and progress tracking. Two popular methods for 3D reconstruction are structure-from-motion (SfM)-based photogrammetry and neural radiance fields (NeRF), a neural network-based technique in computer vision. In this paper, we compare the spatial geometric accuracy of 3D reconstruction from 360° videos of construction sites using the SfM library called Colmap and NeRF. Our experiments show that 3D reconstruction from conventional photogrammetry is sharper than NeRF and more accurate in capturing object details and boundaries.
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Information & Authors
Information
Published In
Computing in Civil Engineering 2023
Pages: 429 - 436
History
Published online: Jan 25, 2024
ASCE Technical Topics:
- Building codes
- Comparative studies
- Computer networks
- Computer vision and image processing
- Computing in civil engineering
- Construction engineering
- Construction management
- Construction sites
- Detection methods
- Engineering fundamentals
- Geomatics
- Methodology (by type)
- Photogrammetry
- Research methods (by type)
- Standards and codes
- Surveying methods
- Tracking
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