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A Quantum Computational Approach to Correspondence Problems on Point Sets
December 13, 2019 Β· Declared Dead Β· π Computer Vision and Pattern Recognition
"No code URL or promise found in abstract"
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Authors
Vladislav Golyanik, Christian Theobalt
arXiv ID
1912.12296
Category
cs.CV: Computer Vision
Cross-listed
cs.ET,
quant-ph
Citations
34
Venue
Computer Vision and Pattern Recognition
Last Checked
4 months ago
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 AQC and derive a new algorithm for correspondence problems on point sets suitable for execution on AQC. Our algorithm has a subquadratic computational complexity of the state preparation. Examples of successful transformation estimation and point set alignment by simulated sampling are shown in the systematic experimental evaluation. Finally, we analyse the differences in the solutions and the corresponding energy values.
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