Hi, I'm working in a museum, currently trying to optically characterize a big historic lens. Unfortunately, it is mounted in a device which can't really be taken apart (issues of conservation), so conventional methods are rather hard to do. I've been loosely following the advances in neural network based approaches ("Two minute papers" kinda stuff) and was wondering if anyone has already realized a solution to my problem using machine learning or similar techniques. That is: Print out a defined optical pattern (like a QR code), "wave" it on one side of the lens and record the image with a camera on the other to get a 3D model of the lens in the end. In my head, it should be possible to train a network using conventional light simulation of randomly generated glass bodies.
Mar-3-2021, 04:00:21 GMT