Fast 3D Point-Cloud Segmentation for Interactive Surfaces

Everett Mondliwethu Mthunzi, Christopher Getschmann, Florian Echtler

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Abstract

Easily accessible depth sensors have enabled using point-cloud data to augment tabletop surfaces in everyday environments. However, point-cloud operations are computationally expensive and challenging to perform in real-time, particularly when targeting embedded systems without a dedicated GPU. In this paper, we propose mitigating the high computational costs by segmenting candidate interaction regions near real-time. We contribute an open-source solution for variable depth cameras using CPU-based architectures. For validation, we employ Microsoft’s Azure Kinect and report achieved performance. Our initial findings show that our approach takes under to segment candidate interaction regions on a tabletop surface and reduces the data volume by up to 70%. We conclude by contrasting the performance of our solution against a model-fitting approach implemented by the SurfaceStreams toolkit. Our approach outperforms the RANSAC-based strategy within the context of our test scenario, segmenting a tabletop’s interaction region up to 94% faster. Our results show promise for point-cloud-based approaches, even when targeting embedded solutions with limited resources.
Original languageEnglish
Title of host publicationISS 2021 - Companion Proceedings of the 2021 Conference on Interactive Surfaces and Spaces
Number of pages5
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery (ACM)
Publication date14 Nov 2021
Pages33–37
ISBN (Electronic)978-1-4503-8340-0
DOIs
Publication statusPublished - 14 Nov 2021
EventISS '21: Interactive Surfaces and Spaces - Lodz, Poland
Duration: 14 Nov 202117 Nov 2021

Conference

ConferenceISS '21: Interactive Surfaces and Spaces
Country/TerritoryPoland
CityLodz
Period14/11/202117/11/2021
SeriesISS '21

Keywords

  • depth cameras
  • fast 3D point-cloud segmentation
  • interactive tabletop surfaces

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