home
***
CD-ROM
|
disk
|
FTP
|
other
***
search
/
vis-ftp.cs.umass.edu
/
vis-ftp.cs.umass.edu.tar
/
vis-ftp.cs.umass.edu
/
pub
/
Text
/
iuw94
/
triangulation.txt
< prev
Wrap
Text File
|
1994-08-19
|
1KB
|
29 lines
Title: Triangulation without Correspondences
Authors: Yong-Qing Cheng, Robert T. Collins,
Allen R. Hanson, Edward M. Riseman
Affiliation: Computer Vision Research Laboratory, Dept. of Computer Science,
University of Massachusetts, Box4610, Amherst, MA. 0l003-4610
Abstract:
This paper presents two different algorithms for reconstructing 3D points
from two sets of noisy 2D image points without knowing point correspondences
given the corresponding poses from the two images. We first present a new way
to form a 2D similarity function between two points from two images via 3D
pseudo-intersection. Based on principles of proximity and exclusion, the
first algorithm uses a new affinity measure between 2D image points from two
different images and a competition scheme to establish image point
correspondences and recover their corresponding 3D points simultaneously.
Based on an optimal graph theoretic approach, the second algorithm uses the
similarity function to construct a bipartite graph, builds a corresponding
flow network, and finally finds a maximum network flow that determines
the correspondences between two images. The two proposed algorithms have been
applied to aerial images from the ARPA RADIUS project. Experimental results
have shown that the proposed algorithms are robust.
Keywords: Triangulation, correspondences, matching, 3D reconstruction,
network flow, principles of proximity and exclusion.