Quantum Motion Segmentation

2022/03/24 by Federica Arrigoni, Arrigoni, Federica, Willi Menapace +7 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · #CCD and CMOS Imaging Sensors #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Quantum Computing Algorithms and Architecture #Spectroscopy Techniques in Biomedical and Chemical Research

paper · pdf · doi:10.48550/arxiv.2203.13185

openalex publication_date 2022/03/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Motion segmentation is a challenging problem that seeks to identify independent motions in two or several input images. This paper introduces the first algorithm for motion segmentation that relies on adiabatic quantum optimization of the objective function. The proposed method achieves on-par performance with the state of the art on problem instances which can be mapped to modern quantum annealers.

Cited by

• Quantum-enhanced Computer Vision: Going Beyond Classical Algorithms

Related

• A Quantum Optimization Method for Geometric Constrained Image Segmentation
• Synthetic Aperture Radar Image Segmentation with Quantum Annealing
• Graph Cut Segmentation Methods Revisited with a Quantum Algorithm
• Quantum Edge Detection for Image Segmentation in Optical Environments
• Adiabatic Quantum Computing for Multi Object Tracking