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2025 | OriginalPaper | Chapter

Robust Fitting on a Gate Quantum Computer

Authors : Frances Fengyi Yang, Michele Sasdelli, Tat-Jun Chin

Published in: Computer Vision – ECCV 2024

Publisher: Springer Nature Switzerland

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Abstract

The chapter delves into the application of quantum computing for robust fitting in computer vision, highlighting the challenges and limitations of classical methods. It introduces a novel quantum circuit for feasibility tests on a gate quantum computer, which was successfully demonstrated on the IonQ Aria quantum computer. The authors also show how Boolean influence computation can be accumulated for more complex estimation tasks, such as fundamental matrix estimation. The work aims to inspire further advancements in quantum-based solutions for computer vision problems.
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Metadata
Title
Robust Fitting on a Gate Quantum Computer
Authors
Frances Fengyi Yang
Michele Sasdelli
Tat-Jun Chin
Copyright Year
2025
Book
Computer Vision – ECCV 2024

Print ISBN: 978-3-031-73231-7

Electronic ISBN: 978-3-031-73232-4

Copyright Year: 2025

DOI
https://doi.org/10.1007/978-3-031-73232-4_7

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