Machine Learning for OpenCV 4 - Second Edition

Generating negatives

The real challenge, however, is to come up with the perfect example of a non-pedestrian. After all, it's easy to think of example images of pedestrians. But what is the opposite of a pedestrian?

This is actually a common problem when trying to solve new machine learning problems. Both research labs and companies spend a lot of time creating and annotating new datasets that fit their specific purpose.

If you're stumped, let me give you a hint on how to approach this. A good first approximation to finding the opposite of a pedestrian is to assemble a dataset of images that look like the images of the positive class but do not contain pedestrians. These images could contain anything like cars, bicycles, streets, houses, ...