Detecting Planar Surfaces in Outdoor Urban Environments

Abstract

We describe an approach to automatically detect building facades in images of urban environments. This is an important problem in vision-based navigation, landmark recognition, and surveillance applications. In particular, with the proliferation of GPS- and camera-enabled cell phones, a backup geolocation system is needed when GPS satellite signals are blocked in so-called "urban canyons." Image line segments are first located, and then the vanishing points of these segments are determined using the RANSAC robust estimation algorithm. Next, the intersections of line segments associated with pairs of vanishing points are used to generate local support for planar facades at different orientations. The plane support points are then clustered using an algorithm that requires no knowledge of the number of clusters or of their spatial proximity. Finally, building facades are identified by fitting vanishing point-aligned quadrilaterals to the clustered support points. Our experiments show good performance in a number of complex urban environments. The main contribution of our approach is its improved performance over existing approaches while placing no constraints on the facades in terms of their number or orientation, and minimal constraints on the length of the detected line segments.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2008
Accession Number
ADA488059

Entities

People

  • Philip David

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Artificial Satellites
  • Computer Vision
  • Computers
  • Environment
  • Geolocation
  • Geometry
  • Global Positioning Systems
  • Information Science
  • Mathematics
  • Mobile Devices
  • Mobile Phones
  • Navigation
  • Orientation (Direction)
  • Position Finding
  • Recognition

Fields of Study

  • Engineering

Readers

  • Computer Networking
  • Computer Vision.
  • Positioning, Navigation, and Timing (PNT) Technology.

Technology Areas

  • Space