8. Stereo processing examples¶
This chapter showcases examples of processing data sets acquired with specific instruments. For a general introduction, see the tutorial (Section 3).
Structure-from-Motion examples are in Section 9 (using a rig and robot images) and in Section 10 (for orbital images with no rig).
- 8.1. Guidelines for selecting stereo pairs
- 8.2. Mars Reconnaissance Orbiter HiRISE
- 8.3. Mars Reconnaissance Orbiter CTX
- 8.4. Automated Processing of HiRISE and CTX
- 8.5. Mars Global Surveyor MOC-NA
- 8.6. Mars Exploration Rovers
- 8.7. K10
- 8.8. Lunar Reconnaissance Orbiter (LRO) NAC
- 8.9. Apollo 15 Metric Camera images
- 8.10. Mars Express High Resolution Stereo Camera (HRSC)
- 8.11. Cassini ISS NAC
- 8.12. Community Sensor Model
- 8.12.1. The USGS CSM Frame sensor
- 8.12.2. The USGS CSM linescan sensor
- 8.12.3. CSM Pushframe sensor
- 8.12.4. The USGS CSM SAR sensor for LRO Mini-RF
- 8.12.5. CSM cameras for MSL
- 8.12.5.1. Illustration
- 8.12.5.2. Fetch the images and metadata from PDS
- 8.12.5.3. Download the SPICE data
- 8.12.5.4. Set up ALE
- 8.12.5.5. Creation of CSM MSL cameras
- 8.12.5.6. Simple stereo example
- 8.12.5.7. Multi-day stereo
- 8.12.5.8. Mapprojection
- 8.12.5.9. MSL Mast cameras
- 8.12.5.10. Low-resolution MSL Nav cam images
- 8.12.6. CSM model state
- 8.12.7. CSM state embedded in ISIS cubes
- 8.13. Dawn (FC) Framing Camera
- 8.14. Kaguya Terrain Camera
- 8.15. LRO Mini-RF using ISIS camera models
- 8.16. Using PBS and SLURM
- 8.17. ASTER
- 8.18. DigitalGlobe
- 8.19. RPC camera models
- 8.20. PeruSat-1
- 8.21. Pleiades
- 8.22. SPOT5
- 8.23. SkySat Stereo and Video data
- 8.23.1. Stereo data
- 8.23.2. Video data
- 8.23.3. The input data
- 8.23.4. Initial camera models and a reference DEM
- 8.23.5. Bundle adjustment
- 8.23.6. Creating terrain models
- 8.23.7. Mosaicking and alignment
- 8.23.8. Alignment of cameras
- 8.23.9. Mapprojection
- 8.23.10. When things fail
- 8.23.11. Structure from motion
- 8.23.12. RPC models
- 8.23.13. Bundle adjustment using reference terrain
- 8.23.14. Floating the camera intrinsics
- 8.24. Declassified satellite images: KH-4B
- 8.24.1. Fetching the data
- 8.24.2. Resizing the images
- 8.24.3. Stitching the images
- 8.24.4. Fetching a ground truth DEM
- 8.24.5. Creating camera files
- 8.24.6. Bundle adjustment and stereo
- 8.24.7. Validation of cameras
- 8.24.8. Running stereo
- 8.24.9. DEM generation and alignment
- 8.24.10. Floating the intrinsics
- 8.24.11. Modeling the camera models as pinhole cameras with RPC distortion
- 8.25. Declassified satellite images: KH-7
- 8.26. Declassified satellite images: KH-9
- 8.27. Shallow-water bathymetry
- 8.27.1. Software considerations
- 8.27.2. Physics considerations
- 8.27.3. Computation of the water-land threshold
- 8.27.4. Creation of masks based on the threshold
- 8.27.5. Determination of the water surface
- 8.27.6. Stereo with bathymetry correction
- 8.27.7. Performing sanity checks on a bathy run
- 8.27.8. Bundle adjustment and alignment
- 8.27.9. Validation of alignment
- 8.27.10. Bathymetry with changing water level
- 8.27.11. How to reuse most of a run
- 8.27.12. Bathymetry correction with mapprojected images
- 8.27.13. Using Digital Globe PAN images
- 8.27.14. Using non-Digital Globe images
- 8.27.15. Effect of bathymetry correction on the output DEM
9. SfM examples using a robot rig¶
These examples shows how to solve for camera poses using Structure-from-Motion (SfM) and then create textured meshes.
The images are acquired using a rig mounted on a robot on the ISS (Section 9.1, Section 9.2) and with the MSL Curiosity rover (Section 9.3).
Somewhat related examples, but without using a rig or the above workflow, are in Section 10 (the images are acquired in orbit using a satellite and a DEM is produced) and Section 8.6 (a basic and rather old two-image example for the MER rovers). See also Section 8.12.5 for an example using CSM cameras for the MSL rover, without employing SfM.
- 9.1. A 3-sensor rig example
- 9.2. Mapping the ISS using 2 rigs with 3 cameras each
- 9.2.1. Illustration
- 9.2.2. Overview
- 9.2.3. Data acquisition strategy
- 9.2.4. Challenges
- 9.2.5. Data processing strategy
- 9.2.6. Installing the software
- 9.2.7. Data preparation
- 9.2.8. A first small run
- 9.2.9. Results
- 9.2.10. Scaling up the problem
- 9.2.11. Fine-tuning
- 9.2.12. Surgery with maps
- 9.2.13. Sample rig configuration
- 9.3. MSL navcam example