Optical flow background subtraction for real-time PTZ camera object tracking

The use of pan/tilt/zoom (PTZ) camera systems with Computer Vision (CV) techniques is a burgeoning field. Utility is most commonly seen with security systems, robotics, navigation and for capturing sports events. This paper seeks to expand the use of PTZ´s in the area of measurement; specifically, the real-time tracking and measurement of Nano/Micro Unmanned Aircraft Systems (UAS). Empirical methods for developing various Nano/Micro UASs, typically ornithopter-related, show possibilities, but require theoretical development for continued understanding and advancements. The study of Nano/Micro UAS state characteristics would enable empirical development by providing supplementary model information for use in finite element and computational fluid dynamics analyses. One such advancement is to develop a metrology system using CV tracking coupled with videogrammetry techniques. The focus of this work is to provide a unique method for obtaining high-resolution, high frame-rate images of a UAS. A novel approach using a Graphics Processing Unit (GPU)-based pyramidal implementation of the Lucas-Kanade feature tracker (i.e. optical flow) to subtract PTZ movement is used to obtain motion measurements for directing the PTZ cameras.