It doesn't contain any new ideas, no - there are many other tutorials about eigenfaces with example code, such as:

http://jeremykun.com/2011/07/27/eigenfaces/

http://nbviewer.ipython.org/github/rcquan/sklearn-practice/b...

The wikipedia article (https://en.wikipedia.org/wiki/Eigenface) also contains code for a MATLAB implementation.

[Author here] Definitely never intended to claim that this was an original discovery; the original paper using the term is ~25 years old [http://www.cs.ucsb.edu/~mturk/Papers/mturk-CVPR91.pdf].

Nonetheless, I've found it to be an interesting concept. There is indeed a homework from the Coursera ML course for computing and visualizing eigenfaces, and the course (and the Stanford CS229 notes) discuss PCA further. I decided to explore the ideas further and distill it into a blog post specifically on eigenfaces.

Goal is for it to serve as a condensed tutorial on an interesting topic! I definitely learned a bunch writing it, and it may be interesting to others who have yet to come across to concept.

The author never implied that this was their own original discovery. Unless they ripped the entire article off, this is just a tutorial on how to work with Eigenfaces on your own, and an explanation of how they work.