The video tutorial demonstrates how to apply Histogram of Oriented Gradients (HOG) to extract features from an image of a truck using Python and OpenCV. It covers loading libraries and images, converting images to grayscale, applying Sobel filters, and implementing HOG to extract and analyze features. The tutorial also explains rescaling intensity for better visualization and discusses using these features in machine learning classifiers to detect objects like cars and trucks.

Describe the process of rescaling intensity in the context of the HOG image.

How can the extracted features be utilized in machine learning?