building positive samples for rotated images for cascaded training in OpenCV
I need to train a cascaded classifier to detect vehicles and different viewing angles. I'm using OpenCV. Some of the angles that I need to capture cause the placement of the vehicle within the image to be diagonal, as shown below: Now the problem with this is that because the vehicle is diagonally placed across the image, then there's a lot of unnecessary background which I can't crop out simply because images have to be rectangular. Is there another way to build positive samples for diagonally placed angles/perspectives of objects? I do need the classifier to be able to recognize this