  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.
