Computer Vision Software Development for an Explosive Seed Pod Trap Camera

Abstract

The purpose of this research is to design a low-cost imaging system for recording the explosive, high velocity behavior of certain seed dispersal events in a natural setting. In particular, the software of this camera features a negative trigger in which a motion-based triggering event (the ejection of seeds) will save as video chips spanning from several seconds before the event to several seconds after the trigger. While easily configurable to take an external trigger, this paper will explore the possibility of using computer vision to serve as the trigger, thereby reducing the need for external sensors. The field-oriented, cost-effective, modular design using a Raspberry Pi will allow for broader applications ranging from wildlife and ecological data acquisition to kinesiological studies requiring spontaneous triggering and lightweight, low cost implementation