Image matching is a fundamental aspect of many problems in computer vision. We describe a novel wide baseline
matching method based on scale invariant feature descriptor. First, corners in image pairs are detected based on an
improved Curvature Scale-Space (CSS) technique. These corners are relatively invariant to affine transformations, and
are represented by using Scale Invariant Feature Transform (SIFT) descriptor to provide robust matching. The nearest
neighbor distance is then applied to remove mismatched corners. Finally, the robust estimation algorithm, RANSAC, is
adopt to estimate the fundamental matrix from the correspondence, and at the same time identify inlying matches.
Experiments demonstrate the feasibility of this method.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.