Mean-shift

Mean-shift is a tracking algorithm. It helps computers keep track of something, like a person or an object, when it is moving around. It works by looking for groups of things that look similar.

When mean-shift is used, the computer looks at something, like an image, and it attempts to find clusters of similar things. For example, if you look at a picture full of red pixels, the computer can group all those red pixels together, since they look the same.

Once the computer finds these clusters, it doesn’t just stop. It then uses those clusters as markers, so it can “track” the object or person as they move around. As the object moves, the computer will update its clusters and keep track of the object.

Mean-shift can be used for a lot of things, like self-driving cars, face recognition, and more. It helps computers “see” and understand their environment better.