Stereo vision is the process of extracting 3D information from multiple 2D views of a scene.
The 3D information can be obtained from a pair of images, also known as a stereo pair, by estimating the relative depth of points in the scene. These estimates are represented in a stereo disparity map, which is constructed by matching corresponding points in the stereo pair.
Stereo images are rectified to simplify matching, so that a corresponding point in one image can be found in the same row in the other image. This reduces the 2D stereo correspondence problem to a 1D problem. Stereo image rectification is achieved by determining a set of matched interest points, estimating the fundamental matrix, and then deriving two projective transformations.
Stereo vision is used in many applications such as robot navigation, 3D movie recording and production, object tracking, machine vision, and range sensing. For more information on stereo vision, see Computer Vision System Toolbox.