From preliminary analysis, it seems that photogrammetry
works better than some modern machine learning techniques at generating
meshes. I plan on developing a pipeline that produces meshes using
photogrammetry and other modern methods such as machine learning, using
different combinations of the number of photos and resolution. The goal is
to analyze and visually compare the error between these meshes to a ground
truth mesh using different uncertainty visualization methods.