A comprehensive survey on Delaunay Triangulation: applications, algorithms, and implementations over CPUs, GPUs, and FPGAs
dc.contributor.author | Elshakhs, Yahia S. | |
dc.contributor.author | Deliparaschos, Kyriakos M. | |
dc.contributor.author | Charalambous, Themistoklis | |
dc.contributor.author | Oliva, Gabriele | |
dc.contributor.author | Zolotas, Argyrios | |
dc.date.accessioned | 2024-03-19T14:27:47Z | |
dc.date.available | 2024-03-19T14:27:47Z | |
dc.date.issued | 2024-01-15 | |
dc.description.abstract | Delaunay triangulation is an effective way to build a triangulation of a cloud of points, i.e., a partitioning of the points into simplices (triangles in 2D, tetrahedra in 3D, and so on), such that no two simplices overlap and every point in the set is a vertex of at least one simplex. Such a triangulation has been shown to have several interesting properties in terms of the structure of the simplices it constructs (e.g., maximising the minimum angle of the triangles in the bi-dimensional case) and has several critical applications in the contexts of computer graphics, computational geometry, mobile robotics or indoor localisation, to name a few application domains. This review paper revolves around three main pillars: (I) algorithms, (II) implementations over central processing units (CPUs), graphics processing units (GPUs), and field programmable gate arrays (FPGAs), and (III) applications. Specifically, the paper provides a comprehensive review of the main state-of-the-art algorithmic approaches to compute the Delaunay Triangulation. Subsequently, it delivers a critical review of implementations of Delaunay triangulation over CPUs, GPUs, and FPGAs. Finally, the paper covers a broad and multi-disciplinary range of possible applications of this technique. | en_UK |
dc.identifier.citation | Elshakhs YS, Deliparaschos KM, Charalambous T, et al., (2024) A comprehensive survey on Delaunay Triangulation: applications, algorithms, and implementations over CPUs, GPUs, and FPGAs. IEEE Access. Volume 12, 2024, pp. 12562-12585 | en_UK |
dc.identifier.issn | 2169-3536 | |
dc.identifier.uri | https://doi.org/10.1109/ACCESS.2024.3354709 | |
dc.identifier.uri | https://dspace.lib.cranfield.ac.uk/handle/1826/21043 | |
dc.language.iso | en_UK | en_UK |
dc.publisher | IEEE | en_UK |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Delaunay triangulation | en_UK |
dc.subject | applications of Delaunay triangulation | en_UK |
dc.subject | algorithmic approaches to Delaunay triangulation | en_UK |
dc.subject | CPU implementation of Delaunay triangulation | en_UK |
dc.subject | GPU implementation of Delaunay triangulation | en_UK |
dc.subject | FPGA implementation of Delaunay triangulation | en_UK |
dc.subject | Voronoi diagram | en_UK |
dc.subject | CPU | en_UK |
dc.subject | GPU | en_UK |
dc.subject | FPGA | en_UK |
dc.title | A comprehensive survey on Delaunay Triangulation: applications, algorithms, and implementations over CPUs, GPUs, and FPGAs | en_UK |
dc.type | Article | en_UK |
dcterms.dateAccepted | 2024-01-10 |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- Survey_on_Delaunay_Triangulation-2024.pdf
- Size:
- 2.47 MB
- Format:
- Adobe Portable Document Format
- Description:
License bundle
1 - 1 of 1
No Thumbnail Available
- Name:
- license.txt
- Size:
- 1.63 KB
- Format:
- Item-specific license agreed upon to submission
- Description: