The Seventh Canadian Conference on Computer and Robot Vision (CRV 2010) is being held right here in Ottawa next week, and I'll be attending at least a couple of the days. A paper I wrote based on some of my Masters work was accepted to be presented there, and I was also invited to give a tutorial on feature detection for the free tutorial day happening on Sunday.
In the paper, I talked about using supplemental information to help make existing SURF and MSER feature descriptors a bit more unique. I found that adding this information didn't help SURF descriptors a whole lot in many cases, but always seemed to improve MSER performance. (If none of that makes any sense to you, basically I just did some stuff to make matching features in images a little bit easier.)
The tutorial is just an overview of some of the different feature detectors and doesn't get into much detail at all. It's only 15 minutes including questions, so there's no point in trying to get too deep into it. My slides are very visual and minimal, but I made a PDF copy of them that includes many notes to be posted on the web.
You can see the Tutorial Day schedule, or look at my slides from the main CRV website. My paper isn't online anywhere yet, but if you want to download and look at my 20 MB thesis file, you can.