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dc.contributor.authorSchmitz, Patricen_US
dc.contributor.authorSuder, Sebastianen_US
dc.contributor.authorSchuster, Kerstenen_US
dc.contributor.authorKobbelt, Leifen_US
dc.contributor.editorBender, Janen_US
dc.contributor.editorBotsch, Marioen_US
dc.contributor.editorKeim, Daniel A.en_US
dc.description.abstractWe 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.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.subjectCCS Concepts: Computing methodologies --> Point-based models; Image processing; Virtual reality
dc.subjectComputing methodologies
dc.subjectbased models
dc.subjectImage processing
dc.subjectVirtual reality
dc.titleInteractive Segmentation of Textured Point Cloudsen_US
dc.description.seriesinformationVision, Modeling, and Visualization
dc.description.sectionheadersSession I
dc.identifier.pages8 pages

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License