Hi r/MachineLearning. I hope this post is welcomed here because I couldn’t think of another better place and I really believe that you guys can help me. In the coming year I will start writing my dissertation. The topic I’m interested in is about Human Activity Recognition. I talked with my advisor professor and we agreed about two approaches:

1. Research oriented. For example coming with different architectures, see what kind of videos are hard for current state of the art methods, etc. From what I saw the datasets are quite big and the current neural networks require few weeks to train and I don’t have access to such computational power. And here comes my first question: given this situation, what are the things you think that I should focus on if I want to go on this route?
2. Doing something practical. For example to recognize the fine-grained actions from a specific sport/activity and to do something with them. The problem here is that there are not too many datasets, and I thought that maybe you know some interesting datasets regarding this aspect.

I have to mention that I personally prefer the first option, but I’m open to suggestions.

Thanks for the help and sorry if I posted in the wrong place.