The paper explores the application of various universal voting schemes, including Plurality Voting, Condorcet Voting, Contingent Voting, Broda Count, and Instant Runoff Voting, in the context of ensemble-based visual place recognition (VPR) systems. The authors aim to determine whether a single optimal voting scheme exists or if the selection of a voting technique is relative to the specific application and environment.
The authors first provide an overview of related work on challenges in the field of VPR and the development of ensemble VPR methods. They then present the methodologies of the different voting schemes and how they are employed in an ensemble VPR setup.
The experimental setup involves testing the voting schemes on various VPR datasets, including GardensPoint, ESSEX3IN1, CrossSeasons, Corridor, 17Places, and Livingroom, using eight state-of-the-art VPR techniques as the ensemble members.
The results are presented in three ways: performance bounds of each voting scheme, precision-recall curves, and a statistical significance analysis using a variant of the McNemar's test. The findings suggest that the selection of a voting scheme significantly impacts the VPR results, and there is no single optimal voting scheme that outperforms the others across all datasets. The performance of the voting schemes varies depending on the dataset and environmental characteristics.
The authors provide a ranking of the voting methods from best to worst, which can guide the selection of an appropriate voting technique for a given VPR application. The statistical analysis further confirms the reliability of the outcomes and the substantial differences in performance between the voting schemes.
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by Maria Waheed... at arxiv.org 05-07-2024
https://arxiv.org/pdf/2405.02297.pdfDeeper Inquiries