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And ...without GPS to provide location data for each image, how did you think you could do photogrammetry?
You don't need positions or attitude info to process pictures with photogrammetric software such as pix4d or Photoscan (or even camera calibration - but it's more debatable).
Even if you record these values, they are just guidelines for the software to help it understand the model and increase processing time, but anyway they are not used as measurments in the processing, all those values are re-calculated. This is what makes photogrammetry with drones efficient, as the tools to measure those values are far from being accurate enough for traditionnal photogrammetric processing. It is compensated mainly by increasing picture overlap and by algorithms based on tie points matching between pictures to calculate all the parameters for each picture (position, attitude and even camera internals).
You can do very accurate photogrammetry from any pictures set, as long as you have strong overlap and a homogenuous ground control points network. I have modeled an indoor miniature park using different camera models (even smartphone), 5000+ pictures (~10 days calculation), none of them geotagged, and just a scale and orientation factor (and a few manual tie points)... I have managed to deliver a survey from the available pictures during the flight that lead to the crash, even if overlap was, for my taste, a bit too low.