Share Email Print

Proceedings Paper

Maximum-weight bipartite matching technique and its application in image feature matching
Author(s): Yong-Qing Cheng; Victor Wu; Robert Collins; Allen R. Hanson; Edward M. Riseman
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

An important and difficult problem in computer vision is to determine 2D image feature correspondences over a set of images. In this paper, two new affinity measures for image points and lines from different images are presented, and are used to construct unweighted and weighted bipartite graphs. It is shown that the image feature matching problem can be reduced to an unweighted matching problem in the bipartite graphs. It is further shown that the problem can be formulated as the general maximum-weight bipartite matching problem, thus generalizing the above unweighted bipartite matching technique.

Paper Details

Date Published: 27 February 1996
PDF: 10 pages
Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); doi: 10.1117/12.233261
Show Author Affiliations
Yong-Qing Cheng, Univ. of Massachusetts/Amherst (United States)
Victor Wu, Univ. of Massachusetts/Amherst (United States)
Robert Collins, Univ. of Massachusetts/Amherst (United States)
Allen R. Hanson, Univ. of Massachusetts/Amherst (United States)
Edward M. Riseman, Univ. of Massachusetts/Amherst (United States)

Published in SPIE Proceedings Vol. 2727:
Visual Communications and Image Processing '96
Rashid Ansari; Mark J. T. Smith, Editor(s)

© SPIE. Terms of Use
Back to Top