This work investigates the process of automating reconstruction of buildings from video imagery. New metrics were developed to detect the least blurred images in a sequence for further processing. Phase correlation for point matching was investigated and new metrics were developed to identify successful matches. Direct relative orientation algorithms were investigated in-depth. A significant finding was a new 6-point algorithm which outperformed previously published algorithms for a number of calibrated camera and target geometries. The development of the new metrics and the outcomes from the comprehensive investigations conducted have contributed to a better understanding of the challenging problem of automatically reconstructing 3D objects from image sequences.
Identifer | oai:union.ndltd.org:ADTP/245217 |
Creators | Fulton, John R. |
Source Sets | Australiasian Digital Theses Program |
Language | English |
Detected Language | English |
Rights | Terms and Conditions: Copyright in works deposited in the University of Melbourne Eprints Repository (UMER) is retained by the copyright owner. The work may not be altered without permission from the copyright owner. Readers may only, download, print, and save electronic copies of whole works for their own personal non-commercial use. Any use that exceeds these limits requires permission from the copyright owner. Attribution is essential when quoting or paraphrasing from these works., Open Access |
Page generated in 0.0014 seconds