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A Quantum Computational Approach to Correspondence Problems on Point Sets

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Golyanik,  Vladislav
Computer Graphics, MPI for Informatics, Max Planck Society;

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Theobalt,  Christian       
Computer Graphics, MPI for Informatics, Max Planck Society;

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arXiv:1912.12296.pdf
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Citation

Golyanik, V., & Theobalt, C. (2019). A Quantum Computational Approach to Correspondence Problems on Point Sets. Retrieved from http://arxiv.org/abs/1912.12296.


Cite as: https://hdl.handle.net/21.11116/0000-0005-7DF0-0
Abstract
Modern adiabatic quantum computers (AQC) are already used to solve difficult
combinatorial optimisation problems in various domains of science. Currently,
only a few applications of AQC in computer vision have been demonstrated. We
review modern AQC and derive the first algorithm for transformation estimation
and point set alignment suitable for AQC. Our algorithm has a subquadratic
computational complexity of state preparation. We perform a systematic
experimental analysis of the proposed approach and show several examples of
successful point set alignment by simulated sampling. With this paper, we hope
to boost the research on AQC for computer vision.