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# Computer Vision System Toolbox

## Stereo Vision

Stereo vision is the process of extracting the 3D structure of a scene from multiple 2D views.

Computer Vision System Toolbox provides functions and algorithms to complete the following steps in the stereo vision workflow:

• Stereo calibration
• Stereo image rectification
• Disparity map computation
• 3D scene reconstruction

### Stereo Calibration

Stereo calibration is the process of finding the intrinsic and extrinsic parameters of a pair of cameras, as well as the relative positions and orientations of the cameras. Stereo calibration is a precursor to calibrated stereo rectification and 3D scene reconstruction. Computer Vision System Toolbox provides algorithms and functions to calibrate a pair of stereo cameras using a checkerboard calibration pattern.

Visualizing the extrinsic parameters of a pair of stereo cameras.

### Stereo Image Rectification

Stereo image rectification transforms a pair of stereo images so that a corresponding point in one image can be found in the corresponding row in the other image. This process reduces the 2-D stereo correspondence problem to a 1-D problem, and it simplifies how to determine the depth of each point in the scene. Computer Vision System Toolbox provides functionality for stereo rectification that includes:

• Uncalibrated stereo rectification using feature matching and RANSAC to estimate the projective transform between cameras
• Calibrated stereo rectification using stereo calibration to compute the fundamental matrix
Results from uncalibrated stereo image rectification. Non-overlapping areas are shown in red and cyan.

### Disparity Computation and 3D Scene Reconstruction

The relative depths of points in a scene are represented in a stereo disparity map which is calculated by matching corresponding points in a pair of rectified stereo images. The system toolbox provides algorithms for disparity calculation including:

• Semi-global matching
• Block matching
Stereo disparity map (right) representing the relative depths of points in a scene (left).

You can reconstruct the 3D structure of a scene by projecting the 2D contents of a scene to three dimensions using the disparity map and information from stereo calibration.

Reconstructing a scene using a pair of stereo images. To visualize the disparity, the right channel is combined with the left channel to create a composite (top left); also shown are a disparity map of the scene (top right) and a 3D rendering of the scene (bottom).