Title page for ETD etd-06222011-124334


Type of Document Master's Thesis
Author Stefanik, Kevin Vincent
Author's Email Address stefanik@vt.edu
URN etd-06222011-124334
Title Sequential Motion Estimation and Refinement for Applications of Real-time Reconstruction from Stereo Vision
Degree Master of Science
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Kochersberger, Kevin Bruce Committee Chair
Abbott, A. Lynn Committee Member
Woolsey, Craig A. Committee Member
Keywords
  • feature points
  • stereo vision
  • bundle adjustment
  • matching
  • UAV
  • SURF
  • 3D reconstruction
  • IRLS
  • terrain mapping
Date of Defense 2011-05-31
Availability unrestricted
Abstract
This paper presents a new approach to the feature-matching problem for 3D reconstruction by taking advantage of GPS and IMU data, along with a prior calibrated stereo camera system. It is expected that pose estimates and calibration can be used to increase feature matching speed and accuracy. Given pose estimates of cameras and extracted features from images, the algorithm first enumerates feature matches based on stereo projection constraints in 2D and then backprojects them to 3D. Then, a grid search algorithm over potential camera poses is proposed to match the 3D features and find the largest group of 3D feature matches between pairs of stereo frames. This approach will provide pose accuracy to within the space that each grid region covers. Further refinement of relative camera poses is performed with an iteratively re-weighted least squares (IRLS) method in order to reject outliers in the 3D matches. The algorithm is shown to be capable of running in real-time correctly, where the majority of processing time is taken by feature extraction and description. The method is shown to outperform standard open source software for reconstruction from imagery.
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