Multi-Sensor Vision Data Fusion for Smart Airborne Surveillance

Abstract

This research addresses the problem of detection and tracking of moving targets of interest within a multi-source data fusion framework that can elegantly integrate vision data captured by airborne optical and infrared (IR) cameras. The system can be employed in tactical airborne surveillance applications that are essential for activity analysis and situation awareness. Complementary information from the optical and IR cameras enables to perceive features in the environment more accurately and reliably. This report describes the research activities and developments during the course of the project.

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Document Details

Document Type
Technical Report
Publication Date
May 01, 2009
Accession Number
ADA499525

Entities

People

  • Aki Sekmen
  • Fenghui Yao

Organizations

  • Tennessee State University

Tags

Communities of Interest

  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Airborne
  • Computer Science
  • Data Fusion
  • Detection
  • Detectors
  • Image Registration
  • Information Systems
  • Moving Targets
  • Optical Images
  • Situational Awareness
  • Surveillance
  • Systems Engineering
  • Target Detection
  • Targets
  • Unmanned Aerial Vehicles
  • Wavelet Transforms

Readers

  • Distributed Systems and Data Platform Development
  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Image Processing and Computer Vision.