In ecological research, accurately collecting spatiotemporal position data is a fundamental task for understanding the behavior and ecology of insects and other organisms. In recent years, advancements in computer vision techniques have reached a stage of maturity where they can support, and in some cases, replace manual observation. In this study, a simple and inexpensive method for monitoring insects in three dimensions (3D) was developed so that their behavior could be observed automatically in experimental environments. The main achievements of this study have been to create a 3D monitoring algorithm using inexpensive cameras and other equipment to design an adjusting algorithm for depth error, and to validate how our plotting algorithm is quantitatively precise, all of which had not been realized in conventional studies. By offering detailed 3D visualizations of insects, the plotting algorithm aids researchers in more effectively comprehending how insects interact within their environments.

翻译：在生态学研究中，精确采集时空位置数据是理解昆虫及其他生物行为与生态的基础任务。近年来，计算机视觉技术的进步已发展至成熟阶段，能够支持甚至在某些场景下替代人工观测。本研究开发了一种简单且低成本的昆虫三维监测方法，可在实验环境中自动观察昆虫行为。主要创新在于：利用廉价摄像设备构建三维监测算法、设计深度误差校正算法，并验证了该轨迹绘图算法的定量精度——这些均为传统研究未实现的目标。该算法通过提供精细的昆虫三维可视化，帮助研究者更有效地理解昆虫与环境间的交互作用。