Real-Time, Multiple, Pan/Tilt/Zoom, Computer Vision Tracking, and 3D Position Estimating System for Unmanned Aerial System Metrology

Abstract

The study of structural characteristics of Unmanned Aerial Systems (UASs) continues to be an important field of research for developing state of the art nano/micro systems. Development of a metrology system using computer vision (CV) tracking and 3D point extraction would provide an avenue for making these theoretical developments. This work provides a portable, scalable system capable of real-time tracking, zooming, and 3D position estimation of a UAS using multiple cameras. Current state-of-the-art photogrammetry systems use retro-reflective markers or single point lasers to obtain object poses and/or positions over time. Using a CV pan/tilt/zoom (PTZ) system has the potential to circumvent their limitations. The system developed in this paper exploits parallel-processing and the GPU for CV-tracking, using optical flow and known camera motion, in order to capture a moving object using two PTU cameras. The parallel-processing technique developed in this work is versatile, allowing the ability to test other CV methods with a PTZ system using known camera motion. Utilizing known camera poses, the object's 3D position is estimated and focal lengths are estimated for filling the image to a desired amount. This system is tested against truth data obtained using an industrial system.

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Document Details

Document Type
Technical Report
Publication Date
Oct 18, 2013
Accession Number
ADA599513

Entities

People

  • Daniel D. Doyle

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Cyber
  • Sensors

DTIC Thesaurus Topics

  • Aircrafts
  • Artificial Intelligence
  • Automata Theory
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computer Vision
  • Control Systems
  • Data Mining
  • Information Processing
  • Information Science
  • Kalman Filters
  • Mathematical Filters
  • Processing Equipment
  • Supervised Machine Learning
  • Unmanned Aerial Systems
  • Unmanned Aerial Vehicles

Fields of Study

  • Computer science

Readers

  • Aerospace Test and Evaluation
  • Computer Vision.

Technology Areas

  • AI & ML
  • Autonomy
  • Directed Energy