I'm an undergraduate taking a deep learning/computer vision class this term, and our final assignment is an open-ended computer vision project. I'm looking for ideas.
Basically, I want something a little novel (perhaps even impressive) that's a departure from the standard image recognition and classification projects that are usually completed as "exercises" for this final project - things like license plate recognition or food classification that tend to be done every year.
For what it's worth, I have a pretty solid background in my CS fundamentals. I'm absolutely willing to consider any project - the ideation process has been pretty tricky thus far. The stack for the class is Python, TensorFlow, and OpenCV.
I've got 2 months to work on this project, and I'm willing to dedicate as much time as needed, so please don't limit ideas to a severe time constraint. I don't have any extra money though, so ideas that need a lot of cloud processing might be out of scope.
Basically output the next N frames, given an input sample. It's trivial to estimate the error as you just split the video in two equal pieces. And try to guess the second half.
And it's so difficult because it's not mere rgb probability. It requires scene understanding. And the physical trajectories of the bodies in motion!
I had the idea that you could take a really basic video game such as pong, snake, space invaders or tetris. And not only predict next frames. But also infer physical quantities from laws of motion.
Being able to apply it to a bullet hell style shmup would very very interesting. As some projectiles use sine waves. And others follow rng random walk paths ;)