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

Abstract

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.