发表机构
Hong Kong Center for Construction Robotics（香港建造机器人中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对无人机立面异常筛查中RGB与热成像的几何失配问题，提出含配准与带符号局部对比度编码的传感器级融合流水线，并构建M3T数据集，实验表明该方法在分层检测上优于RGB基线。
AI 中文摘要
无人机立面检查可将红绿蓝（RGB）图像与热测量相结合，以筛查表面和亚表面异常。然而，传感器之间的几何差异和热图像渲染可能会掩盖空间对应关系和微弱的温度对比。本文提出了一种传感器级流水线，包括逐传感器校正、RGB到热成像配准、公共支持区域裁剪以及16位辐射测量值的带符号局部对比度编码。该编码保留了局部较热与较冷区域之间的区别，并为紧凑型单流检测器提供第四输入通道。我们引入了M3T数据集，该数据集包含来自五个立面检查项目的674对配对的RGB和辐射热样本，涵盖八种构件和异常类别。中位残余配准误差为3.384像素，受控位移分析表征了局部对比度响应在受控位移下的变化。按项目分组的四折评估在交并比阈值0.5至0.95范围内产生平均精度均值0.168，每幅图像使用285亿次浮点运算。单独的单一分割消融实验显示，与仅使用RGB和替代热输入相比，分层检测性能有所提升，尽管总体精度并未优于仅使用RGB。在RGBT-Tiny上的评估显示，使用渲染热图像时性能参差不齐。这些结果表征了对齐辐射对比度在紧凑型立面筛查中的类别特定优势与局限性。
英文摘要
Unmanned aerial vehicle facade inspection can combine red, green, and blue (RGB) imagery with thermal measurements to screen surface and subsurface anomalies. However, geometric discrepancies between the sensors and thermal image rendering can obscure spatial correspondence and weak temperature contrasts. This article presents a sensor-level pipeline comprising per-sensor correction, RGB-to-thermal registration, common-support cropping, and signed local contrast encoding of 16-bit radiometric measurements. The encoding preserves the distinction between locally hotter and colder regions and supplies the fourth input channel of a compact single-stream detector. We introduce M3T, a dataset of 674 paired RGB and radiometric thermal samples from five facade-inspection projects covering eight component and anomaly categories. The median residual registration error is 3.384 pixels, and a controlled-displacement analysis characterizes how the local contrast response changes under controlled displacement. Project-grouped four-fold evaluation yields mean average precision of 0.168 over intersection-over-union thresholds from 0.5 to 0.95, using 28.50 billion floating-point operations per image. A separate single-split ablation shows improved delamination detection over RGB-only and alternative thermal inputs, although aggregate accuracy does not improve over RGB alone. Evaluation on RGBT-Tiny shows mixed performance with rendered thermal imagery. These results characterize the category-specific benefits and limitations of aligned radiometric contrast for compact facade screening.
Comments9 pages, 3 figures. Preprint. Submitted to IEEE Sensors Journal
