1992
@incollection{CHL1992,
vgclass = {refpap},
vgproject = {invariance},
author = {Christopher Coelho and Aaron Heller and Joseph L. Mundy
and David A. Forsyth and Andrew Zisserman},
title = {An Experimental Evaluation of Projective Invariants},
editor = {Joseph Mundy and Andrew Zisserman},
booktitle = {Geometric Invariance in Computer Vision},
address = {Cambridge, MA, USA},
series = {Series: Artificial intelligence},
pages = {87--104},
publisher = {The MIT Press},
year = {1992},
abstract = {Projective invariants are being used in vision
applications with increasing frequency. This paper addresses the
question of reliability of five commonly used planar projective
invariants given the types of errors encountered in actual
applications. They are analyzed from a theoretical viewpoint to derive
expressions that characterize the propagation of error and from an
experimental viewpoint by constructing test patterns with known values
of the invariants and comparing these to the values calculated from
image data. We discover that the accuracy and stability of the
invariants are directly dependent on the performance of the feature
extraction scheme employed to recover the test pattern geometry from
the images. Because of this, we are able to devise a feature extractor
testing methodology based on planar projective invariants. Preliminary
results from tests on three different feature extractors are
presented.},
}