Interactive Segmentation of Textured Point Clouds

Patric Schmitz, Sebastian Suder, Kersten Schuster, Leif Kobbelt
International Symposium on Vision, Modeling, and Visualization 2022

We present a method for the interactive segmentation of textured 3D point clouds. The problem is formulated as a minimum graph cut on a k-nearest neighbor graph and leverages the rich information contained in high-resolution photographs as the discriminative feature. We demonstrate that the achievable segmentation accuracy is significantly improved compared to using an average color per point as in prior work. The method is designed to work efficiently on large datasets and yields results at interactive rates. This way, an interactive workflow can be realized in an immersive virtual environment, which supports the segmentation task by improved depth perception and the use of tracked 3D input devices. Our method enables to create high-quality segmentations of textured point clouds fast and conveniently.

» Show BibTeX

@inproceedings {10.2312:vmv.20221200,
booktitle = {Vision, Modeling, and Visualization},
editor = {Bender, Jan and Botsch, Mario and Keim, Daniel A.},
title = {{Interactive Segmentation of Textured Point Clouds}},
author = {Schmitz, Patric and Suder, Sebastian and Schuster, Kersten and Kobbelt, Leif},
year = {2022},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-189-2},
DOI = {10.2312/vmv.20221200}

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