TITLE:
Two-Edge-Corner Image Features for Registration of Geospatial Images with Large View Variations
AUTHORS:
Parvaneh Saeedi, Mao Mao
KEYWORDS:
Image Variant Features, Geometrical Image Features, Feature Grouping, Large View Variation, Match Correspondences
JOURNAL NAME:
International Journal of Geosciences,
Vol.5 No.11,
October
27,
2014
ABSTRACT: This paper presents a robust
image feature that can be used to automatically establish match correspondences
between aerial images of suburban areas with large view variations. Unlike most
commonly used invariant image features, this feature is view variant. The
geometrical structure of the feature allows predicting its visual appearance
according to the observer’s view. This feature is named 2EC (2 Edges and a
Corner) as it utilizes two line segments or edges and their intersection or
corner. These lines are constrained to correspond to the boundaries of
rooftops. The description of each feature includes the two edges’ length, their
intersection, orientation, and the image patch surrounded by a parallelogram
that is constructed with the two edges. Potential match candidates are obtained
by comparing features, while accounting for the geometrical changes that are
expected due to large view variation. Once the putative matches are obtained,
the outliers are filtered out using a projective matrix optimization method.
Based on the results of the optimization process, a second round of matching is
conducted within a more confined search space that leads to a more accurate
match establishment. We demonstrate how establishing match correspondences
using these features lead to computing more accurate camera parameters and
fundamental matrix and therefore more accurate image registration and 3D
reconstruction.