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Automated Visual Database Creation For A Ground Vehicle Simulator

Abstract

dc:description.abstract

This research focuses on extracting road models from stereo video sequences taken from a moving vehicle. The proposed method combines color histogram based segmentation, active contours (snakes) and morphological processing to extract road boundary coordinates for conversion into Matlab or Multigen OpenFlight compatible polygonal representations. Color segmentation uses an initial truth frame to develop a color probability density function (PDF) of the road versus the terrain. Subsequent frames are segmented using a Maximum Apostiori Probability (MAP) criteria and the resulting templates are used to update the PDFs. Color segmentation worked well where there was minimal shadowing and occlusion by other cars. A snake algorithm was used to find the road edges which were converted to 3D coordinates using stereo disparity and vehicle position information. The resulting 3D road models were accurate to within 1 meter.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Claudio, Pedro
Contributors dc:contributor
  • Bauer, Christian

Subjects

dc:subject × 6

Rights

Language dc:language
English

Identifiers

dc:identifier.*
Identifier
CFE0001326
OAI identifier oai:identifier
oai:stars.library.ucf.edu:etd-1997

Chain of custody

source
Harvested from
Central Florida
Base URL
stars.library.ucf.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Claudio, Pedro. Automated Visual Database Creation For A Ground Vehicle Simulator. 2006. https://stars.library.ucf.edu/etd/998