For the last 2 weeks i have been refactoring my code and getting it to run en mass on all the different grozi images. I have finished my first full run of all the data, it all runs on many machines and can be done in around 6 hrs!! The first pass through the data is promising for surf, but rather depressing for HAAR . I found a bug in my code that probably makes it very unlikely for it to detect anything. Thus, I am in the process of retraining. As far as the SURF data goes, its pretty promising, in general its very good for objects that have a clear number of really strong features. though some items that are rather small or are easily deformed are not nearly as easily detected.
After the data is done training, I intend on moving forward on building out the final system. This will basically involve incorporating the first level classifier that I am getting from the project in cse 254 and then running detection on that. Assuming that we get reasonable performance with haar for an item it would be best to cascade from chm->haar-> sift as the total time to detection would be something near 1 sec using all 3 approaches.
Meanwhile, I am chugging along with my project in yoav's class in trying to determine the presence or absence of items. Go there to see more of which direction we are going with that.