Affine-Invariant Curve Matching
Marco Zuliani, Sitaram Bhagavathy, B. S. Manjunath, and C. S. Kenney
Department of Electrical and Computer Engineering
University of California, Santa Barbara, CA 93106.
{zuliani, sitaram, manj, kenney} [at] ece.ucsb.edu
Department of Electrical and Computer Engineering
University of California, Santa Barbara, CA 93106.
{zuliani, sitaram, manj, kenney} [at] ece.ucsb.edu
Abstract
In this paper, we propose an affine-invariant method for describing and matching curves. This is important since affine transformations are often used to model perspective distortions. More specifically, we propose a new definition of the shape of a curve that characterizes a curve independently of the effects introduced by affine distortions. By combining this definition with a rotation-invariant shape descriptor, we show how it is possible to describe a curve in an intrinsically affine-invariant manner. To validate our procedure we built a database of shapes subject to perspective distortions and plotted the precision-recall curve for this dataset. Finally an application of our method is shown in the context of wide baseline matching.
IEEE International Conference on Image Processing, Singapore, Oct. 2004.
Node ID: 379 ,
DB ID: 177 ,
VRLID: 138 ,
Lab: VRL ,
Target: Conference
Subject: [Image Registration and Fusion] « Look up more