Training custom SVM to use with HOGDescriptor in OpenCV

Question

I\'m trying to train my own detector for use with OpenCV::HOGDescriptor but I\'m having trouble making the existing HOGDescriptor work with my newly trained SVM.

I

Answer 1

From what I read in Dalal's paper about HOG detector, he suggest that to remove false positives, we need to retrain our model. Retraining is done by applying preliminary model (your model which gives lot of false positives), then detect objects in all negative sample images. All of returned rectangles would definitely false positives.

Then, add all of these false positives to your negative sample images (negative dataset), do training once again. The resulting model, as suggested in the paper, will return much less false positives.

Unfortunately though, I tried that (re-training), but the resulting model just does not recognize anything, even on positive image samples. But I think it is worth a try because that was what suggested in the inventor's paper about HOG detector