# Part Segmentation of 3D Point Clouds with OpenVINO™

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Point clouds are an important type of geometric data structure. OpenVINO can directly consume point cloud data and perform inference with it.

## Notebook Contents

This notebook demonstrates how to process [point cloud](https://en.wikipedia.org/wiki/Point_cloud) data and run 3D Part Segmentation with OpenVINO. The inputs of this task are a collection of individual data points in a three-dimensional plane with each point having a set coordinates on the X, Y, and Z axes.

This notebook uses a pre-trained [PointNet](https://arxiv.org/abs/1612.00593) model to detect each part of a chair and return its category.


## Installation Instructions

This is a self-contained example that relies solely on its own code.</br>
We recommend running the notebook in a virtual environment. You only need a Jupyter server to start.
For details, please refer to [Installation Guide](../../README.md).