Splitting image dataset with few subjects but many data
I think you're hitting on the fact that by training and testing on the same subjects your model is not going to be able to generalize to new subjects very well. If you're only interested predicting emotions for these subjects, you are taking the right approach. However, if you want to generalize your model to new, unseen subjects, you should split your training and testing sets such that subjects in the training set are not in the test set, and vice versa to get a more accurate test score. Most likely it will not perform as well and you should consider collecting more data on new subjects if possible.

Here is a similar question on Stack Exchange.