Abstract
High-speed video can provide fine-scaled analysis of animal behavior. However, extracting behavioral data from video sequences is a time-consuming, tedious, subjective task. These issues are exacerbated where accurate behavioral descriptions require analysis of multiple points in three dimensions. We describe a new computer program written to assist a user in simultaneously extracting three-dimensional kinematics of multiple points on each of an insect's six legs. Digital video of a walking cockroach was collected in grayscale at 500 fps from two synchronized, calibrated cameras. We improved the legs' visibility by painting white dots on the joints, similar to techniques used for digitizing human motion. Compared to manual digitization of 26 points on the legs over a single, 8-second bout of walking (or 106,496 individual 3D points), our software achieved approximately 90% of the accuracy with 10% of the labor. Our experimental design reduced the complexity of the tracking problem by tethering the insect and allowing it to walk in place on a lightly oiled glass surface, but in principle, the algorithms implemented are extensible to free walking. Our software is free and open-source, written in the free language Python and including a graphical user interface for configuration and control. We encourage collaborative enhancements to make this tool both better and widely utilized.
Highlights
Students of animal behavior have long recognized the importance of high-speed videography to understanding the mechanisms of locomotion
As high-speed cameras have improved and become more widely available, more and more insights have been achieved in animal behavior and neuroscience (e.g., [1,2,3,4,5])
Many parameters of insect walking have remained unanalyzed by previous investigators due to the difficulties of collecting the large kinematic datasets necessary to unravel the complicated mechanics of these overactuated systems
Summary
Students of animal behavior have long recognized the importance of high-speed videography to understanding the mechanisms of locomotion. These investigations, tracing their roots to the famous horse photography of Eadweard Muybridge in the 1870s, have remained in the mind of ethologists to the present day. The majority of analysis consists of an operator manually selecting points of interest in frame after frame of video, digitizing or extracting an animated sequence of motion. Is this tedious and time-consuming, it is subjective. It seems as if the ever-increasing speed of desktop computers should have something to offer
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