DCK, this is what I use
1. Import Images
In Camera Groups
2. Check Camera Calibration + Rolling Shutter
Tools > Camera Calibration
3. Convert GPS coordinates of your geotagged images (WGS84) to match the coordinate system of your ground control poins (GCPs) which will be imported later
4. Estimate image quality
View -> Photos -> Detailed View -> Menu -> Estimate Image Quality
Disable all images that have an image quality below 0.7
5. Generate masks (Optional)
if for example, you don't want to include cars or other moving objects. Optional.
6. Align photos HIGH
Pair preselection: REFERENCE
Key point limit: 40,000
Tie point limit: 4,000
Adaptive camere model fitting: YES
Note that you do not need to run the image alignment process twice if you follow this workflow.
7. Import list of Ground Control Points
also include the X/Y/Z accuracy values
8. Refine GCP
Select single markers & filter fotos
9. Verify and link markers to images (use FILTER BY MARKERS). Because the acquired images and the markers now have the same coordinate reference system, it should be easy to find and mark your GCPs in your images. Mark each GCP in 3-6 images. That should be sufficient. When finished, press the UPDATE button in the reference pane.
10. Assuming that you have a sufficient number of high accuracy ground control points, uncheck all images in the reference pane and also uncheck a few GCPs in order to use them as check points instead of control points. This will give you a better measure of the 'real accuracy' of your dataset.
11. Clean Sparse Point Cloud
> Model > Gradual Selection
Remove all points with high reprojection error of >1
Remove all points with high reconstruction uncertainty >100
12. Adjust your bounding box
13. Optimize camera alignment
All settings
14. Build Dense Cloud
High