Object recognition using a dynamic relaxation method

D. J. Pack, L. Neal, L. Tamburino, M. E. Minardi
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引用次数: 2

Abstract

In this paper, we show a novel approach for solving the classical feature matching problem between a pair of predicted and extracted images. Point features are considered, and the feature matching is performed using a dynamic relaxation method. The proposed method examines the evidence in the local neighborhoods of a possible matching predicted and extracted feature pair and determines the validity of the current match. The advantage of the proposed method is that the match process is performed simultaneously for all possible matching features. The simultaneous process allows a set of possible matching pairs to compete against other sets of possible matching pairs without putting any restrictions on the order of which a match must be performed. The method may be especially attractive when the geometric relationships between features in an image are unclear. We demonstrate the effectiveness of the proposed method using several examples.
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目标识别采用动态松弛方法
在本文中,我们展示了一种新的方法来解决一对预测和提取图像之间的经典特征匹配问题。考虑点特征,采用动态松弛法进行特征匹配。该方法对可能匹配的预测和提取的特征对的局部邻域内的证据进行检验,并确定当前匹配的有效性。该方法的优点是对所有可能的匹配特征同时执行匹配过程。同时处理允许一组可能的匹配对与其他可能的匹配对进行竞争,而无需对必须执行匹配的顺序施加任何限制。当图像中特征之间的几何关系不清楚时,该方法可能特别有吸引力。我们用几个例子证明了所提方法的有效性。
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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