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Paper

A Quantum Computational Approach to Correspondence Problems on Point Sets

MPS-Authors
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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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Fulltext (public)

arXiv:1912.12296.pdf
(Preprint), 2MB

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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: http://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.