Your points on MV are not unfounded, but they are also extremely homeocentric. All of your examples rely on the visible light spectrum as well as standard “vision” as we know it. Realistically any sensor can be used to generate an image if you know what you are doing with it. Radio telescopes are a great example of this. There is also a lot of research going on in giving AI’s MV senses access to other sections of the EM spectrum ( https://www.edge-ai-vision.com/2017/10/beyond-visible-light-applications-in-computer-vision/ and https://www.technologyreview.com/2019/10/09/132696/machine-vision-has-learned-to-use-radio-waves-to-see-through-walls-and-in-darkness/ ) as well as echolocation ( https://www.imveurope.com/news/echolocation-neural-net-gives-phones-3d-vision-sound ). There are many other types of “vision” that can be used that can definitely distinguish a popcan.