More Progress

This last week I tried a couple of things. First was instead of trying the comparision of lots of random points, I tried comparing random lines. This, didn't not work anywhere near as well as the random points did. The first major setback was how slow it was compared to random points. Maybe this was just because it was done in matlab, but comparing 100 random lines was slower than 4000 random points (and I usually don't use 4000 points). And with 100 random lines, there was not enough data for effective detection.

After that I went with another suggestion from class, and that was the idea of background subtraction. Using Kinect gives a unique feature that you don't get from RGB data, that is you can make assumtions about what is the background and then get rid of it. So I modified my image converting script to do background subtraction.

Example of image with background subtraction. The background is gone! (and replaced with black)

Also collected a lot more data labeling negitives and positives that I believed would help my results the most. The most recent results where ran with 120 positive and 600 negitive labels. Some of the test images included Xs that WERE NOT in the positive training examples, and Xs where still detected just as well as the Xs that were in the training data. Results will be in a future post.