Now that I am about to graduate, my Ph.D. adviser, Troy, and I have identified a volunteer research project on which I can collaborate. Troy’s GRIME Lab is working with collaborators in the U.S., Europe, and Latin America to develop methods for the crowd sourcing of hydrologically interesting water scene images. With this project, the biggest problem is figuring out how to extract meaningful information from the images. There is quite a bit of mostly failed work on extracting information from unconditioned images–that is, images where there is nothing in the scene to help calibrate the images so that measurements can be taken. Our plan is to take a step back, make minor changes to the staff gauges that are commonly in those scenes and see if we can start gathering more meaningful information than what is already there. The problem with that is the size of the calibration target (the octagon in the scene) is very small compared to what we used during my Ph.D. research. It looks, though, like I can find the target fine. The problem then is to figure out how to make the calibration right after the target is found.