Interactive Segmentation of Textured Point Clouds

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Date
2022
Journal Title
Journal ISSN
Volume Title
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.
Description

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
} }
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