This paper deals with 3D-modeling from images of moving camera. The solution of 3D modeling is based on principle of LSQ-estimation, that the increasing number of observations is inversely proportional to effect of noise to estimation. The idea of the algorithm is to gather observations of linear features from multiple time varying video frames and perform simultaneous intersection and resection, i.e. triangulation, of 3D features. The observations are extracted from images by involving Hough transformation for edges detected by typical edge detector. All remaining pixels are used as observations for estimating feature parameters and intersection points of featuers as well as camera pose and orientation in 3D space. The algorithm presented here is off-line process where observations are gathered as background process. To combine observations from multiple frames feature feature matching has to be performed. To improve robustness of matching operator can add some constraints to matching process.

Date Published: 13 September 1995
PDF: 9 pages
Proc. SPIE 2598, Videometrics IV, (13 September 1995); doi: 10.1117/12.220906

Published in SPIE Proceedings Vol. 2598:
Videometrics IV
Sabry F. El-Hakim, Editor(s)