Tracking termites: computer vision tools for termitologists

Quantifying movement patterns of organisms creates the possibility of a scientific and data driven analysis of recurring behavioral events and interactions within an insect population under study. With the modern technological advances, gathering data of this kind is made easier in the sense that a larger number of tools and techniques are at disposal of the interested party. Here we present a set of these tools created using digital image processing and computer vision methods, of tracking termites on experiments video footage made at the Federal University of Viçosa Termitology Lab. Using the Python’s language OpenCV library, the devised package submits an image sequence to analysis, identify the termites present at the movie, and tracks these individuals along time, reporting their position in the frame, the distances between them and who they are colliding with. The collected information is then presented to the user in a useful graphical form. For a performance demonstration, a case study is presented at the end of this paper where we show the movement analysis output of a termite mold population sample recorded at a Petri plate during one of our routine experiments