Infrared thermal imaging is a passive imaging technique that captures the emitted radiation from an object to estimate surface temperature, often for inference of heat transfer. Infrared thermal imaging offers the potential to detect movement without the challenges of glare, shadows, or changes in lighting associated with visual digital imaging or active infrared imaging. In this paper, we employ a frame subtraction algorithm for extracting the pixel-by-pixel relative change in signal from a fixed focus video file, tailored for use with thermal imaging videos. By summing the absolute differences across an entire video, we are able to assign quantitative activity assessments to thermal imaging data for comparison with simultaneous recordings of metabolic rates. We tested the accuracy and limits of this approach by analyzing movement of a metronome and provide an example application of the approach to a study of Darwin's finches. In principle, this "Difference Imaging Thermography" (DIT) would allow for activity data to be standardized to energetic measurements and could be applied to any radiometric imaging system.

中文翻译：

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使用差分成像方法的热成像视频活动分析

红外热成像是一种被动成像技术，它捕获物体发出的辐射以估计表面温度，通常用于推断热传递。红外热成像提供了检测运动的潜力，而没有与视觉数字成像或主动红外成像相关的眩光、阴影或照明变化的挑战。在本文中，我们采用帧减法算法从固定焦距视频文件中提取信号的逐像素相对变化，该文件专为热成像视频而设计。通过对整个视频的绝对差异求和，我们能够将定量活动评估分配给热成像数据，以便与同时记录的代谢率进行比较。我们通过分析节拍器的运动测试了这种方法的准确性和局限性，并提供了该方法在达尔文雀研究中的应用示例。原则上，这种“差分成像热成像”(DIT) 将允许将活动数据标准化为能量测量，并可应用于任何辐射成像系统。