Robust Data Alignment and its Application in an Integrated Multi-Sensor Surveillance System Consisting of UAVs and Fixed Platforms. The Current and Future Phase of the RASER Project

Abstract

This report introduces a new algorithm called Robust Data Alignment (RDA) for persistent sensing in multi-layered sensor network. Invariant features collected from a set of images are used for image registration. Information-theoretic cost models a functional structure where an optimal transformation can be recovered from feature representations of different but related images. By using a cooperative search strategy, we believe that RDA can help to understand and deal with many situations in persistent sensor networks by solving problems such as Layered sensing, Multi-modal data fusion, Multi-UAV sensing. In addition, we provide Georegistration for CLIF 2007 dataset. SIFT algorithm after georeferencing recovers a correspondence for data registration.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2009
Accession Number
ADA502286

Entities

People

  • Jonathan Martin
  • K. Redmill
  • S. Jwa
  • U. Ozguner

Organizations

  • Ohio State University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Algorithms
  • Computer Graphics
  • Cost Models
  • Data Fusion
  • Detection
  • Detectors
  • Feature Extraction
  • Image Processing
  • Image Registration
  • Infrared Detectors
  • Layered Sensing
  • Sensor Networks
  • Target Recognition
  • Two Dimensional
  • Unmanned Aerial Vehicles

Fields of Study

  • Computer science

Readers

  • Aerial Unmanned Vehicle Swarm Micro Periodontal Dentistry.
  • Distributed Systems and Data Platform Development
  • Sensor Fusion and Tracking Systems.