Thanks for these suggestions, Cody! I'll work on testing them out tomorrow and reporting back. A few other follow-up comments:
--For "right tilt", I mean tilting the top of the camera towards the right, so the bottom right of the camera is lower than the top left of the camera, or rotating clockwise when looking through the viewfinder.
--For my last sentence, I meant projected instead of converted. We originally had lat/long for our location in WGS-84; I reprojected to Web Mercator.
--We are using a Canon 7D. I was able to extract focal length from the image's exif data. I calculated A0, A1, A2, B0, B1 and B2 using the pixel to microns value for the camera and the equation I found here: http://proceedings.esri.com/library/userconf/devsummit16/papers/dev_int_237.pdf. And I estimated the principal point as the center of the image. Based on sample data I found online, I assumed this was the midpoint as 0, 0.
--Our original test images were from a fixed location on a building down to the ground. Our real data are images collected from an aircraft of harbor seal haulout locations in Alaska. We use a Canon 7D with a Solmeta attached (for heading, pitch and roll). The camera is not fixed to the plane; rather hand-held and photos are only taken when harbor seal haulout locations are surveyed. There is a fair amount of overlap at some sites; and at other sites, there may only be one image. Our final product will be a number of orthorectified surfaces (one for each haulout) or a single surface (with large gaps between haulout locations), depending on what works best for counting/digitizing harbor seals from the images. Currently, individual seals are counted and the location is just the geo-tagged location where the image was taken. We would like to improve our counting to get georeferenced locations of at least the image, if not of the individual seals within the haulout.
--I am currently using ArcGIS Pro 2.0.