Interactive Segmentation of Textured Point Clouds

Schmitz, Patric; Suder, Sebastian; Schuster, Kersten; Kobbelt, Leif

Interactive Segmentation of Textured Point Clouds

Files

025-032.pdf (3.03 MB)

paper1012_mm.mp4 (98.19 MB)

Date

2022

Authors

Schmitz, Patric
Suder, Sebastian
Schuster, Kersten
Kobbelt, Leif

Publisher

The Eurographics Association

Abstract

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.

CCS Concepts: Computing methodologies --> Point-based models; Image processing; Virtual reality

        @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
}
}