BlendPCR: Seamless and Efficient Rendering of Dynamic Point Clouds captured by Multiple RGB-D Cameras

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dc.contributor.authorMühlenbrock, Andreen_US
dc.contributor.authorWeller, Reneen_US
dc.contributor.authorZachmann, Gabrielen_US
dc.contributor.editorHasegawa, Shoichien_US
dc.contributor.editorSakata, Nobuchikaen_US
dc.contributor.editorSundstedt, Veronicaen_US
dc.date.accessioned2024-11-29T06:43:07Z
dc.date.available2024-11-29T06:43:07Z
dc.date.issued2024
dc.description.abstractTraditional techniques for rendering continuous surfaces from dynamic, noisy point clouds using multi-camera setups often suffer from disruptive artifacts in overlapping areas, similar to z-fighting. We introduce BlendPCR, an advanced rendering technique that effectively addresses these artifacts through a dual approach of point cloud processing and screen space blending. Additionally, we present a UV coordinate encoding scheme to enable high-resolution texture mapping via standard camera SDKs. We demonstrate that our approach offers superior visual rendering quality over traditional splat and mesh-based methods and exhibits no artifacts in those overlapping areas, which still occur in leading-edge NeRF and Gaussian Splat based approaches like Pointersect and P2ENet. In practical tests with seven Microsoft Azure Kinects, processing, including uploading the point clouds to GPU, requires only 13.8 ms (when using one color per point) or 29.2 ms (using high-resolution color textures), and rendering at a resolution of 3580 x 2066 takes just 3.2 ms, proving its suitability for real-time VR applications.en_US
dc.description.sectionheadersRendering and Sensing
dc.description.seriesinformationICAT-EGVE 2024 - International Conference on Artificial Reality and Telexistence and Eurographics Symposium on Virtual Environments
dc.identifier.doi10.2312/egve.20241366
dc.identifier.isbn978-3-03868-245-5
dc.identifier.issn1727-530X
dc.identifier.pages10 pages
dc.identifier.urihttps://doi.org/10.2312/egve.20241366
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/egve20241366
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Rendering; Virtual reality; Point-based models; Mesh geometry models
dc.subjectComputing methodologies → Rendering
dc.subjectVirtual reality
dc.subjectPoint
dc.subjectbased models
dc.subjectMesh geometry models
dc.titleBlendPCR: Seamless and Efficient Rendering of Dynamic Point Clouds captured by Multiple RGB-D Camerasen_US
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