# Robust Subpixel Localization of Diagonal Markers in Large-Scale Navigation via Multi-Layer Screening and Adaptive Matching

arXiv: https://arxiv.org/abs/2601.08161 · HTML: https://mlsanity.com/paper/2601.08161/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 8 of its 41 references that are in the map.
- First posted on arXiv 13 Jan 2026.

## Builds on (most cited first, 8 of 8)

- [Robust and Precise Vehicle Localization based on Multi-sensor Fusion in Diverse City Scenes](https://mlsanity.com/paper/1711.05805/) (2017)
- [Stereo Event-based, 6-DOF Pose Tracking for Uncooperative Spacecraft](https://mlsanity.com/paper/2503.12732/) (2025)
- [Dynamic Event Camera Calibration](https://mlsanity.com/paper/2107.06749/) (2021)
- [Event-based multi-view photogrammetry for high-dynamic, high-velocity target measurement](https://mlsanity.com/paper/2506.00578/) (2025)
- [Simultaneous Enhancement and Noise Suppression under Complex Illumination Conditions](https://mlsanity.com/paper/2512.08378/) (2025)
- [Accurate Pose Estimation for Flight Platforms based on Divergent Multi-Aperture Imaging System](https://mlsanity.com/paper/2502.19708/) (2025)
- [Optimizing Fiducial Marker Placement for Improved Visual Localization](https://mlsanity.com/paper/2211.01513/) (2022)
- [Collimator-assisted high-precision calibration method for event cameras](https://mlsanity.com/paper/2512.16092/) (2025)

## Abstract (arXiv)

This paper proposes a robust, high-precision positioning methodology to address localization failures arising from complex background interference in large-scale flight navigation and the computational inefficiency inherent in conventional sliding window matching techniques. The proposed methodology employs a three-tiered framework incorporating multi-layer corner screening and adaptive template matching. Firstly, dimensionality is reduced through illumination equalization and structural information extraction. A coarse-to-fine candidate selection strategy minimizes sliding window computational costs, enabling rapid estimation of the marker's position. Finally, adaptive templates are generated for candidate points, achieving subpixel precision through improved template matching with correlation coefficient extremum fitting. Experimental results demonstrate the method's effectiveness in extracting and localizing diagonal markers in complex, large-scale environments, making it ideal for field-of-view measurement in navigation tasks.