Pedestrian detection using HOG

The Histogram of Oriented Gradients (HOG) is an object detection technique implemented by OpenCV. In simple cases, it can be used to see whether there is a certain object present in the image, where it is, and how big it is.

OpenCV includes a detector trained for pedestrians, and you are going to use it. It might not be enough for a real-life situation, but it is useful to learn how to use it. You could also train another one with more images to see whether it performs better. Later in the book, you will see how to use deep learning to detect not only pedestrians but also cars and traffic lights.

Sliding window

The HOG pedestrian detector in OpenCV is trained with a model that is 48x96 pixels, and therefore it is not able to detect objects smaller than that (or, better, it could, but the box will be 48x96).

At the core of the HOG detector, there is a mechanism able to tell whether a given 48x96 image is a pedestrian. As this is not terribly...