I'm reading this computer vision paper, research paper link, about creating a model to estimate the real age and perceived age of the person in the image (or at least that's what I think it's about). The perceived age is decided by this method: each image is looked at by 10 independent individuals and they estimate the age of the person. The mean and standard deviation are taken from the age guesses of the 10 individuals.
The paper then goes on to use an epsilon error by this equation as part of the model evaluation for perceived age and state the following
the evaluation employs fitting a normal distribution with the mean µ and standard deviation σ of the votes for each image. The paper also says that this epsilon error covers the aspect of the uncertainty of the ground truth age.
The results are then posted in a table showing different epsilon error values based on different models.
My questions are the following:
What is that equation and is it standardly used? It says
What is x in this equation? I thought it was some type of feature scaling of the image but that makes no sense because the results are all different in the table and completely out of context anyway. Is x supposed to be the predicted age?