1. 1
Photogrammetry on Cloud using Photoscan
Raminder Singh
Research Data Services
Research Technologies, Indiana University
May 18, 2016

2. 2
Agisoft’s Photoscan
• Photoscan is a professional-level GUI based tool to process a collection of images into dense point
clouds as well as textured meshes.
• It has a batch mode, but the processing stages must be entered by hand using the GUI for each
collection to be processed.
• The dense point cloud generation stage can take advantage of GPU hardware.

3. 3
Photoscan’s Pros and Cons
Pros
– Usually higher-quality output (more points, less fringing)
– Batch queue allows the entire workflow to be specified at the beginning
– Some stages will take advantage of GPU processors
Cons
– GUI interface requires manual intervention (minimally to setup a batch)

4. 4
Data Sets
• Doll: 61 images, 14 Mpix each, Size: 350MB.
http://www.agisoft.com/downloads/sample-data/
• IU Venus: 80 images. 24 Mpix each, Size: 500MB
• Niobid F3 statue from Bernie Frischer:
151 images. 24 Mpix each, Size: 2.08 GB
(with 8 cores – 1 GPU node NVIDIA drive -
Processed in ~9 hours )

5. 5
Microsoft Azure Configurations and Costing (~ $100 per core/per month)

6. 6
Azure: Comparison Charts for CPU and Memory
2 cores - 90 mins 4 cores - 50 mins 8 cores - 30 mins

7. 7
Azure: CPU, Memory and File I/O with 2 cores

8. 8
Azure: CPU, Memory and File I/O with 2 cores

9. 9
Azure: CPU, Memory and File I/O with 2 cores

10. 10
Azure: CPU, Memory and File I/O with 4 cores

11. 11
Azure: CPU, Memory and File I/O with 8 cores

12. 12
Monthly Sponsorship Statement for period 4/1/2016 through 4/30/2016

13. 13
Conclusion with Azure
• Observations on PhotoScan:
– Photoscan is CPU intensive, memory does not matter, 14GB was good enough.
– Batch mode works but its best to stop after photo alignment for selection of area for better results.
– Sketchfab link: https://skfb.ly/NOzL
• Using premium storage is expensive and we need to know when its required.
• No GPU nodes.
– Availability announced in Sep 2015.
– Prerelease version is not available.
• Issue on monitoring and accounting:
– Its hard to create reports and customize dashboards on Azure.
– We are not able to get to daily account information based on usage.

14. 14
AWS Configurations and Costing

15. 15
AWS: Comparison Charts for Instance Hours

16. 16
AWS: Comparison Charts for Instance Costs

17. 17
Timing and Dense point cloud results by Bill Sherman
Pixels VisualSFM PhotoScan
Niobid Quarter 0.22GP (147x1004x1504) ___ / 0.36M 695m / 3.5M
Niobid Half 0.89GP (148x2008x3008) 910m / 1.2M ~2460 / 14.5M
Niobid Full 3.58GP (148x4016x6016) ~140m / 5.2M (*) ~7200m / 45.0M
HummingBird 0.13GP (26x2500x2000) 18.5m / 0.50M ___ / 0.65M
ClockAtArb 4.35GP (207x5616x3744) 310m / 3.4M 77m / 4.8M
(*) Run by Chris Eller on ADAM-1 workstation at 16 core and GPUs
* Niobid Full was also run by Tassie Gniady on Momento. Process time (including mesh creation) was approximately 180m. Mesh has obvious
issues with the intricacies of the hand (see screenshot below).