Comparison of GPU-based Methods for Handling Point Cloud Occlusion

Simple item page
dc.contributor.authorLópez, Alfonsoen_US
dc.contributor.authorJurado, Juan Manuelen_US
dc.contributor.authorPadrón, Emilio Joséen_US
dc.contributor.authorOgayar, Carlos Javieren_US
dc.contributor.authorFeito, Francisco Ramónen_US
dc.contributor.editorOrtega, Lidia M. and Chica, Antonioen_US
dc.date.accessioned2021-09-21T08:09:01Z
dc.date.available2021-09-21T08:09:01Z
dc.date.issued2021
dc.description.abstractThree-dimensional point clouds have conventionally been used along with several sources of information. This fusion can be performed by projecting the point cloud into the image plane and retrieving additional data for each point. Nevertheless, the raw projection omits the occlusion caused by foreground surfaces, thus assigning wrong information to 3D points. For large point clouds, testing the occlusion of each point from every viewpoint is a time-consuming task. Hence, we propose several algorithms implemented in GPU and based on the use of z-buffers. Given the size of nowadays point clouds, we also adapt our methodologies to commodity hardware by splitting the point cloud into several chunks. Finally, we compare their performance through the response time.en_US
dc.description.sectionheadersShort Papers
dc.description.seriesinformationSpanish Computer Graphics Conference (CEIG)
dc.identifier.doi10.2312/ceig.20211364
dc.identifier.isbn978-3-03868-160-1
dc.identifier.pages43-46
dc.identifier.urihttps://doi.org/10.2312/ceig.20211364
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/ceig20211364
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectMassively parallel algorithms
dc.subjectVisibility
dc.subjectPoint based models
dc.titleComparison of GPU-based Methods for Handling Point Cloud Occlusionen_US
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
043-046.pdf
Size:
8.13 MB
Format:
Adobe Portable Document Format
Download
Collections
CEIG2021