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MatcherCompass: A Deployment-Aware Benchmark to Guide Image Matcher Selection in the Wild

arXiv · AI, language, vision and robotics · article · Sep 22, 2026 · UTC

Field robots operating across time of day and sensing modalities require accurate image correspondences within onboard time and resource budgets. However, accuracy and runtime reported for individual methods on a single device provide limited guidance for choosing a matcher and its configuration on a target platform. We present MatcherCompass, a deployment-aware benchmark for choosing local feature matchers in field robotics. Under common input and pose-evaluation procedures, we compare nine classical and learned matching pipelines across four image resolutions and supported numerical precisio

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