Scipediacontent: Scipediacontent moved page Draft Content 402979334 to Feld et al 2020a

2021-02-03T17:31:00Z

Scipediacontent moved page Draft Content 402979334 to Feld et al 2020a

Scipediacontent: Created page with " == Abstract == The compression of geometry data is an important aspect of bandwidth-efficient data transfer for distributed 3d computer vision applications. We propose a qua..."

2021-02-03T17:30:57Z

Created page with " == Abstract == The compression of geometry data is an important aspect of bandwidth-efficient data transfer for distributed 3d computer vision applications. We propose a qua..."

New page

== Abstract ==

The compression of geometry data is an important aspect of bandwidth-efficient data transfer for distributed 3d computer vision applications. We propose a quantum-enabled lossy 3d point cloud compression pipeline based on the constructive solid geometry (CSG) model representation. Key parts of the pipeline are mapped to NP-complete problems for which an efficient Ising formulation suitable for the execution on a Quantum Annealer exists. We describe existing Ising formulations for the maximum clique search problem and the smallest exact cover problem, both of which are important building blocks of the proposed compression pipeline. Additionally, we discuss the properties of the overall pipeline regarding result optimality and described Ising formulations.

Comment: 6 pages, 3 figure

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/2003.13253 http://arxiv.org/abs/2003.13253]

* [http://arxiv.org/pdf/2003.13253 http://arxiv.org/pdf/2003.13253]

* [http://xplorestaging.ieee.org/ielx7/8633356/8644067/08644358.pdf?arnumber=8644358 http://xplorestaging.ieee.org/ielx7/8633356/8644067/08644358.pdf?arnumber=8644358],
: [http://dx.doi.org/10.1109/glocomw.2018.8644358 http://dx.doi.org/10.1109/glocomw.2018.8644358]

* [https://dblp.uni-trier.de/db/journals/corr/corr2003.html#abs-2003-13253 https://dblp.uni-trier.de/db/journals/corr/corr2003.html#abs-2003-13253],
: [https://arxiv.org/pdf/2003.13253 https://arxiv.org/pdf/2003.13253],
: [https://arxiv.org/abs/2003.13253 https://arxiv.org/abs/2003.13253],
: [https://ui.adsabs.harvard.edu/abs/2020arXiv200313253F/abstract https://ui.adsabs.harvard.edu/abs/2020arXiv200313253F/abstract],
: [http://export.arxiv.org/pdf/2003.13253 http://export.arxiv.org/pdf/2003.13253],
: [https://fr.arxiv.org/abs/2003.13253 https://fr.arxiv.org/abs/2003.13253],
: [https://ru.arxiv.org/abs/2003.13253 https://ru.arxiv.org/abs/2003.13253],
: [https://www.arxiv-vanity.com/papers/2003.13253 https://www.arxiv-vanity.com/papers/2003.13253],
: [https://au.arxiv.org/abs/2003.13253 https://au.arxiv.org/abs/2003.13253],
: [https://export.arxiv.org/abs/2003.13253 https://export.arxiv.org/abs/2003.13253],
: [https://academic.microsoft.com/#/detail/2920627991 https://academic.microsoft.com/#/detail/2920627991]

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Feld et al 2020a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 402979334 to Feld et al 2020a

Scipediacontent: Created page with " == Abstract == The compression of geometry data is an important aspect of bandwidth-efficient data transfer for distributed 3d computer vision applications. We propose a qua..."