Having a fast Object Recognition Algorithm is essential for many computer vision applications, such as an augmented reality, robotics and self-driving cars. These kinds of applications need to respond to input video streams in real time, and so time is critical. A self-driving car for example, needs to constantly check whether another cars in front of it, so that it can decide whether to slow down, brake, or accelerate. Similarly, augmented reality applications rely on a live view of the real world to decide where to place virtual elements in a given scene. For these real-time applications to work, they need to be able to identify the objects in their field of view, in a fast and efficient manner. This is where ORB comes in. The ORB algorithm is used to quickly create feature vectors of key points in an image. These feature vectors can then be used to identify objects in images. In this lesson, we’ll look at the details of how the ORB algorithm works.