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Iterative Closest Point (ICP)

Introduction

This package is a implementation of the Iterative Closest Point (ICP) algorithm to match point clouds in Tensorflow. It determines the translation and scale parameter between the datasets along a specified set of axes (see Zinßer et al. Point Set Registration with Integrated Scale Estimation). It can handle datasets of an arbitrary number of dimension and runs on multiple CPUs and on GPU.

Requirements

The package is tested and working with Tensorflow 1.14. Other required packages are specified in the requirements file.

Methods of installation

To install the repository from scratch, clone it to your computer using

git clone https://github.com/VincentStimper/icp.git

then go to the folder and install using pip

pip install --upgrade .

or use python directly in the main folder

python setup.py install

Update to the latest version directly from source

pip install --upgrade git+https://github.com/VincentStimper/icp.git

About

Tensorflow implementation of the iterative closest point (ICP) algorithm determining a translation and scaling along specified axes

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