An Iterative Method for Improving Feature Matches

Author

Furch, Johannes ; Eisert, Peter

Author_Institution

Fraunhofer HHI, Humboldt Univ. Berlin, Berlin, Germany

fYear

2013

fDate

June 29 2013-July 1 2013

Firstpage

406

Lastpage

413

Abstract

Finding reliable and well distributed keypoint correspondences between images of non-static scenes is an important task in Computer Vision. We present an iterative algorithm that improves a descriptor Based matching result by enforcing local smoothness. During the optimization process, a Delaunay triangulation of the current set of matches is dynamically maintained. This 2D mesh provides natural neighborhoods and local affine transformations that are used to remove outliers and to resolve ambiguities. The optimization results in a decrease of incorrect correspondences and a significant increase in the total number of matches. The runtime of the overall algorithm is by far dictated by the descriptor Based matching.

Keywords

computer vision; feature extraction; image matching; iterative methods; mesh generation; optimisation; transforms; 2D mesh; Delaunay triangulation; computer vision; descriptor based matching; feature match improvement; iterative method; keypoint correspondences; local affine transformations; local smoothness; natural neighborhoods; nonstatic scenes; optimization process; Heuristic algorithms; Impedance matching; Iterative methods; Optimization; Reliability; TV; Three-dimensional displays;

fLanguage

English

Publisher

ieee

Conference_Titel

3D Vision - 3DV 2013, 2013 International Conference on

Conference_Location

Seattle, WA

Type

conf

DOI

10.1109/3DV.2013.60

Filename

6599103