# Real-Time Fusion of Visual and Chart Data for Enhanced Maritime Vision Source: [Real-Time Fusion of Visual and Chart Data for Enhanced Maritime Vision]() Collection index: [llms.txt]() Data updated: 2025-10-28T13:57:19.334Z Authors: Marten Kreis, Benjamin Kiefer Published: 2025-07-18T12:58:11.000Z ## Abstract This paper presents a novel approach to enhancing marine vision by fusing real-time visual data with chart information. Our system overlays nautical chart data onto live video feeds by accurately matching detected navigational aids, such as buoys, with their corresponding representations in chart data. To achieve robust association, we introduce a transformer-based end-to-end neural network that predicts bounding boxes and confidence scores for buoy queries, enabling the direct matching of image-domain detections with world-space chart markers. The proposed method is compared against baseline approaches, including a ray-casting model that estimates buoy positions via camera projection and a YOLOv7-based network extended with a distance estimation module. Experimental results on a dataset of real-world maritime scenes demonstrate that our approach significantly improves object localization and association accuracy in dynamic and challenging environments. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Vision-to-Chart buoy association on ATON (val)](): Vision-to-Chart buoy association; ATON (val); Precision (P): 79.7. ## Original sources and implementation [Original paper]() [PDF]()