User-Driven Geolocation of Untagged Desert Imagery Using Digital Elevation Models

Abstract

We propose a system for user-aided visual localization of desert imagery without the use of any metadata such as GPS readings, camera focal length, or field-of-view. The system makes use only of publicly available digital elevation models (DEMs) to rapidly and accurately locate photographs in non-urban environments such as deserts. Our system generates synthetic skyline views from a DEM and extracts stable concavity-based features from these skylines to form a database. To localize queries, a user manually traces the skyline on an input photograph. The skyline is automatically refined based on this estimate, and the same concavity-based features are extracted. We then apply a variety of geometrically constrained matching techniques to efficiently and accurately match the query skyline to a database skyline, thereby localizing the query image. We evaluate our system using a test set of 44 ground-truthed images over a 10;000 km2 region of interest in a desert and show that in many cases, queries can be localized with precision as fine as 100m2.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2013
Accession Number
ADA586695

Entities

People

  • Andrew Zhai
  • Avideh Zakhor
  • Eric Tzeng
  • Matthew Clements
  • Raphael Townshend

Organizations

  • University of California, Berkeley

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Cameras
  • Change Detection
  • Computer Science
  • Computer Vision
  • Databases
  • Electrical Engineering
  • Elevation
  • Environment
  • Feature Extraction
  • Geolocation
  • Hash Tables
  • Images
  • Models
  • Pattern Recognition
  • Photographs

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Database Systems and Applications

Technology Areas

  • Space