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.
Highlighted Topics
- Read, Write, and Store Point Clouds
I/O operations to read, write, and store point cloud data - Display Point Clouds
Display and compare 3-D point clouds and play 3-D point cloud video - Point Cloud Registration
Transform and register 3-D point clouds - Point Cloud Fitting to Geometric Shapes
Fit 3-D point clouds to cylinder, plane, and sphere geometric shapes - Point Cloud Utilities
Downsampling, denoising, merging, and normals estimation of 3-D point clouds
Featured Examples
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