What the math courses don't teach us.....

Phew! This has been a long break in my blogging career. More like a sabbatical. Well, between the last blog time and now there have been many updates in my personal and professional life. Rather than getting bored with them I will be talking about some of the technical aspects of whatever I learnt - What the math courses that we do in our college don't teach us?
I have gone through many wierd courses which were always a pain and considered useless. Topology, algebra, finite element methods to name some. No you don't need to go in for wiki to know what these courses are about. It turns out that these courses form the basis of computer science. Alas, the profs could have told us this and we could have been more interested.
First of all, knowing about eigen vectors and the concepts of principal component analysis seemed to be too mathematical to help us in later lives. In reality, computer vision forms most of its theories around these concepts. I read plenty of papers about face comparison techniques available and the most basic one that came out in 1991 used principal component analysis. In layman language, PCA is used if we want to reduce the dependency to lesser parameters(components). This uses the eigen vector approach to work.
People who already knew this please don't hit me:D Others who are looking for more explanation could send me comments about the same:)