Title
Self-Calibrated Reconstruction Of Partially Viewed Symmetric Objects
Abstract
The traditional stereo reconstrction techniques based on point correspondences and the estimation of the cameras from the fundamental matrix introduce a four-fold ambiguity. Moreover, there is a projective ambiguity inherent in the fundamental matrix. We show that a symmetric object can be modeled even under partial occlusion with a pair of uncalibrated stereo images. This implies that unlike traditional stereo algorithms, we can extract 3D information from two arbitrary viewpoints, even when there is no left-to-right point correspondences. To demonstrate the effectiveness of the method, we present experimental results on both synthetic and real images. © 2005 IEEE.
Publication Date
12-1-2005
Publication Title
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume
II
Number of Pages
-
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/ICASSP.2005.1415543
Copyright Status
Unknown
Socpus ID
33646766132 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/33646766132
STARS Citation
Foroosh, Hassan; Balci, Murat; and Cao, Xiaochun, "Self-Calibrated Reconstruction Of Partially Viewed Symmetric Objects" (2005). Scopus Export 2000s. 3335.
https://stars.library.ucf.edu/scopus2000/3335