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Stereo Vision

Stereo rectification, disparity, and dense 3-D reconstruction

Stereo vision is the process of recovering depth from camera images by comparing two or more views of the same scene. The output of this computation is a 3-D point cloud, where each 3-D point corresponds to a pixel in one of the images.

Stereo image rectification projects images onto a common image plane in such a way that the corresponding points have the same row coordinates. This process is useful for stereo vision, because the 2-D stereo correspondence problem reduces to a 1-D problem. As an example, stereo image rectification is often used as a pre-processing step for computing disparity or creating anaglyph images.


Camera CalibratorEstimate geometric parameters of a single camera
Stereo Camera CalibratorEstimate geometric parameters of a stereo camera


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triangulate3-D locations of undistorted matching points in stereo images
undistortImageCorrect image for lens distortion
undistortPointsCorrect point coordinates for lens distortion
cameraMatrixCamera projection matrix
estimateCameraMatrixEstimate camera projection matrix from world-to-image point correspondences
disparityBMCompute disparity map using block matching
disparitySGMCompute disparity map through semi-global matching
estimateUncalibratedRectificationUncalibrated stereo rectification
rectifyStereoImagesRectify a pair of stereo images
reconstructSceneReconstruct 3-D scene from disparity map
stereoParametersObject for storing stereo camera system parameters
stereoAnaglyphCreate red-cyan anaglyph from stereo pair of images
pcshowPlot 3-D point cloud
plotCameraPlot a camera in 3-D coordinates
rotationMatrixToVectorConvert 3-D rotation matrix to rotation vector
rotationVectorToMatrixConvert 3-D rotation vector to rotation matrix


Coordinate Systems

Specify pixel Indices, spatial coordinates, and 3-D coordinate systems

Stereo Camera Calibrator App

Calibrate a stereo camera, which you can then use to recover depth from images.

Featured Examples