In computer vision, the indexing problem is the problem of recognizing a few objects in a large database of objects while avoiding the help of the classical image-feature-to-object-feature matching paradigm. In this paper we address the problem of recognizing 3-D polyhedral objects from 2-D images by indexing. Both the objects to be recognized and the images are represented by weighted graphs. The indexing problem is therefore the problem of determining whether a graph extracted from the image is present or absent in a database of model graphs. We introduce a novel method for performing this graph indexing process which is based both on polynomial characterization of binary and weighted graphs and on hashing. We describe in detail this polynomial characterization and then we show how it can be used in the context of polyhedral object recognition. Next we describe a practical recognition-by-indexing system that includes the organization of the database, the representation of polyhedral objects in terms of 2-D characteristic views, the representation of this views in terms of weighted graphs, and the associated image processing. Finally, some experimental results allow the evaluation of the system performance.

翻译：在计算机视觉中，索引问题是指在大规模对象数据库中识别少量对象时，避免依赖经典图像特征到对象特征匹配范式的问题。本文研究通过索引从二维图像识别三维多面体对象的问题。待识别的对象与图像均采用加权图表示，因此索引问题即判别从图像提取的图是否存在于模型图数据库中。我们提出一种新颖的图索引方法，该方法基于二值图与加权图的多项式表征及哈希技术。首先详细阐述该多项式表征，继而展示其在多面体目标识别中的应用。随后介绍一个实用的识别-索引系统，涵盖数据库组织、基于二维特征视图的多面体对象表示、对应特征视图的加权图表示以及相关图像处理。最后通过实验评估系统性能。