Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling
Abstract
:1. Introduction
- (i)
- It works for images recorded in moderately turbid waters with non-uniform lighting.
- (ii)
- It does not assume scene rigidity; moving features are automatically detected and extracted from the scene. If the moving object appears in more than a few frames, the reconstructed scene will contain occluded regions.
- (iii)
- It allows large datasets and the investigation of structural complexity at multiple extents and resolutions (mm2 to km2).
- (iv)
- It allows in situ data acquisition in a non-intrusive way, including historical datasets.
- (v)
- It enables deployment from multiple imaging-platforms.
- (vi)
- It can obtain measurement accuracies <1 mm, given that at least one landmark of known size is present to extract scale information. Note that as the reconstruction is performed over a larger area its resolution will decrease.
2. Materials and Methods
2.1. Data Acquisition
2.1.1. Calibrated Data: Coral Colony
2.1.2. Uncalibrated Data: Reef Area and Reef Transect
2.2. Image Processing
2.3. Reconstruction Overview
2.3.1. Structure-from-Motion (SfM)
2.3.2. Depth of Field-of-View
2.3.3. Implicit Surface Reconstruction
2.4. Model Reconstruction and Validation
2.4.1. Branching Coral Colony 3D Model
2.4.2. Reef Area and Reef Transect 3D Model
Reef Area Validation Data
Reef Area Underwater 3D Model Reconstruction
Reef Area Underwater 3D Model Validation
Reef Transect Underwater 3D Model Reconstruction
Reef Transect Underwater 3D Model Validation
3. Results
3.1. Branching Coral: Laser-Scanned Model vs. Underwater 3D Model
3.2. Reef Area: In Situ Metrics vs. Underwater 3D Model Metrics
3.3. Reef Transect: In Situ Metrics vs. Underwater 3D Model Metrics
4. Discussion
4.1. Methodological Accuracy and Validation
4.2. Advantages of This Framework
4.3. Limitations and Further Improvements of This Framework
4.4. Ecological Applications
5. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Ferrari, R.; McKinnon, D.; He, H.; Smith, R.N.; Corke, P.; González-Rivero, M.; Mumby, P.J.; Upcroft, B. Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling. Remote Sens. 2016, 8, 113. https://doi.org/10.3390/rs8020113
Ferrari R, McKinnon D, He H, Smith RN, Corke P, González-Rivero M, Mumby PJ, Upcroft B. Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling. Remote Sensing. 2016; 8(2):113. https://doi.org/10.3390/rs8020113
Chicago/Turabian StyleFerrari, Renata, David McKinnon, Hu He, Ryan N. Smith, Peter Corke, Manuel González-Rivero, Peter J. Mumby, and Ben Upcroft. 2016. "Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling" Remote Sensing 8, no. 2: 113. https://doi.org/10.3390/rs8020113
APA StyleFerrari, R., McKinnon, D., He, H., Smith, R. N., Corke, P., González-Rivero, M., Mumby, P. J., & Upcroft, B. (2016). Quantifying Multiscale Habitat Structural Complexity: A Cost-Effective Framework for Underwater 3D Modelling. Remote Sensing, 8(2), 113. https://doi.org/10.3390/rs8020113