Documentation

This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English verison of the page.

Note: This page has been translated by MathWorks. Please click here
To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

3-D Point Cloud Processing

Downsample, denoise, transform, visualize, register, and fit geometrical shapes of 3-D point clouds

Point clouds are typically used to measure physical world surfaces. They have applications in robot navigation and perception, depth estimation, stereo vision, visual registration, and in advanced driver assistance systems (ADAS). Computer Vision System Toolbox™ algorithms provide point cloud processing functionality for downsampling, denoising, and transforming point clouds. The toolbox also provides point cloud registration, geometrical shape fitting to 3-D point clouds, and the ability to read, write, store, display, and compare point clouds. You can also combine multiple point clouds to reconstruct a 3-D scene using the iterative closest point (ICP) algorithm.

Featured Examples