解决高低分辨率红外与可见光相机标定难题，实现精准空间对齐。
On RGB-TIR Stereo Calibration under Extreme Resolution Asymmetry
- 用可切换图案的OLED屏生成可控对比，适配低分辨率红外图像
- 在80×62像素红外图像上实现稳定角点检测，误差仅0.382像素
- 适合建筑热能评估等多模态视觉应用，尤其适用于低成本红外设备
RGB-热红外（TIR）双目相机系统的精确几何标定对多模态建筑表皮分析至关重要，但当使用低分辨率低成本热成像传感器时仍具挑战。本文提出一种实用的双目标定框架，针对分辨率为2028×1520像素的RGB相机与仅80×62像素的TIR相机（像素比约1:625）的极端分辨率差异。采用主动OLED屏幕在单一物理表面上动态切换模态专用图案（热红外用棋盘格，可见光用ChArUco），提供受控且可重复的热对比。设计了一种结合透视校正、Hessian鞍点分析与Mean Shift局部定位的角点检测算法，在80×62像素的红外图像上实现无需逐帧调参的可靠检测。基于基线约束的束调整法克服平面标定物带来的退化问题，获得32.7毫米（标称30毫米）的立体基线，整体重投影误差为0.382像素。在具有热活性的建筑模型上通过恒定深度与逐像素深度估计进行验证，结果表明红外到可见光的投影一致，适用于建筑能耗评估。
原文摘要 · Abstract (English)
Accurate geometric calibration of RGB-thermal infrared (TIR) stereo camera systems is essential for multimodal building envelope analysis, yet remains challenging when low-cost thermal sensors with very low spatial resolution are employed. This paper presents a practical stereo calibration framework for an RGB camera (2028 x 1520 px) paired with a TIR camera operating at only 80 x 62 px - a pixel-count ratio of approximately 1:625. An active OLED screen dynamically switches modality-specific patterns (checkerboard for TIR, ChArUco for RGB) on a single physical surface, providing controlled and repeatable thermal contrast. A dedicated corner detection algorithm combining perspective rectification, Hessian saddle-point analysis, and Mean Shift localisation achieves reliable checkerboard detection at 80 x 62 px without per-frame parameter tuning. A baseline-constrained bundle adjustment enforces physically consistent rig geometry under the planar-calibration-object degeneracy, yielding a stereo baseline of 32.7 mm (nominal 30 mm) with an overall reprojection error of 0.382 px. The system is validated on a thermally active building mock-up using constant-depth and per-pixel depth estimation, demonstrating consistent TIR-to-RGB projection suitable for building energy performance assessment.
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