4 ms·
Isn't this one of the homework's in the stanford/coursera ml course? I feel like this is not really original content
by ibebrett 12y ago
Isn't this one of the homework's in the stanford/coursera ml course? I feel like this is not really original content
- RIMR 12y agoThe 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.
- jamessb 12y agoIt 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://jeremykun.com/2011/07/27/eigenfaces/ http://nbviewer.ipython.org/github/rcquan/sklearn-practice/blob/master/pca_eigenfaces.ipynb http://nbviewer.ipython.org/github/rcquan/sklearn-practice/b... The wikipedia article (https://en.wikipedia.org/wiki/Eigenface https://en.wikipedia.org/wiki/Eigenface) also contains code for a MATLAB implementation.
- dusenberrymw 12y ago[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 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.