SVMs

So I installed, trained, and ran SVMLight today. I used some images which weren't part of the training set and which were taken on completely different days than those taken for the training set (ie, no obviously similar images being used to train and test at the same time). However, these images were quite a bit larger than those that I trained on. I figure that because the features being used right now are color histograms and because this test was only to help me get my bearings, the difference in the sizes of the images wouldn't be extremely important for now. In the end, the SVM got 73% accuracy on the test set (58 pos detect, 21 neg detect), which I find encouraging for a first step.

One of the things I am considering doing next is relabeling my training set so that there are only non-occluded parking spaces being trained on. I also want to gather a more images to both increase the training set and also build a more realistic pseudo-test set. Lastly, I'm going to code up a program for visualizing the SVM's classification guesses overlaid on the test images if I have time.