Sunday, February 28, 2010

Mosaicing

So as to deal with the computation time we have applied optical flow to make sure that we only process a very small set of new pixels at each time step. This drastically reduces computation time, and as you can see still produces a good set of features.



Next step: start applying some detection algorithms to these points.



As you can see I got the old cascade working on it, just i forgot to make it output its final surf homographies, still works thou.

Wednesday, February 24, 2010

Full system!!

So far all this has been about running and training a bunch of different algorithms for the hope that we could one day apply them to actually detecting groceries.



Note that the video is not actually running in real time.

Friday, February 19, 2010

Data Update

So I worked with my code some more, got a few more promising results from HAAR, but still nothing amazing. The results can be seen here

Wednesday, February 17, 2010

Update

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.
http://grozi.calit2.net/grozi.html

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.