Covariant-conics decomposition of quartics for 2D object recognition and affine alignment

Jean-Philippe Tarel, W. Wolovich, D. Cooper
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引用次数: 10

Abstract

This paper outlines a geometric parameterization of 2D curves where the parameterization is in terms of geometric invariants and terms that determine an intrinsic coordinate system. Thus, we present a new approach to handle two fundamental problems: single-computation alignment and recognition of 2D shapes under affine transformations. The approach is model-based, and every shape is first fit by an implicit fourth degree (quartic) polynomial. Based on the decomposition of this equation into three covariant conics, we are able to define a unique intrinsic reference system that incorporates usable alignment information contained in the implicit polynomial representation, a complete set of geometric invariants, and thus an associated canonical form for a quartic. This representation permits shape recognition based on 8 affine invariants. This is illustrated in experiments with real data sets.
二维目标识别和仿射对准的四分位数协变-圆锥分解
本文概述了二维曲线的几何参数化,其中参数化是根据几何不变量和确定内在坐标系的项进行的。因此,我们提出了一种新的方法来处理两个基本问题:单计算对齐和仿射变换下二维形状的识别。该方法是基于模型的,每个形状首先由隐式四次(四次)多项式拟合。基于将该方程分解为三个协变二次曲线,我们能够定义一个独特的内在参照系,该参照系包含了隐多项式表示中包含的可用的排列信息,一组完整的几何不变量,以及四次的相关标准形式。这种表示允许基于8个仿射不变量的形状识别。这在真实数据集的实验中得到了说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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