Key points/pairs

Key points, also known as feature points or interest points, are distinct and unique points in an image that are easy to find and accurately describe. These points are usually selected because they represent corners, edges, or other interesting aspects of the image, and they are used in many computer vision tasks for things like object recognition, image alignment, and 3D reconstruction.

When multiple images are used (for example, in a video or a sequence of frames taken by a moving robot), pairs of key points can be identified. A key point in one image is paired with the same key point in another image. This can be done by describing the key points using a feature descriptor (a numerical representation of the local image around the key point), and then matching these descriptions between images.

This process of identifying key point pairs is a crucial step in many computer vision tasks. For example:

In image stitching (like creating a panorama from multiple photos), key point pairs are used to align the images with each other.
In structure from motion or SLAM (Simultaneous Localization and Mapping), key point pairs are used to reconstruct 3D structure and camera movement from a series of 2D images.

For a rescue robot, this process can be useful in multiple ways. For example, by identifying key point pairs between consecutive frames taken by the robot's camera, the robot can estimate its own movement and build up a 3D map of its environment. This can help the robot navigate effectively, recognize objects or people, and understand its surroundings.