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A Performance Characterization Algorithm for Symbol Localization

机译:符号定位的性能表征算法

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In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more "reliable" and "open" solution to characterize the performance. To achieve that, it exploits only single points as the result of localization and offers the possibility to reconsider the localization results provided by a system. We use the information about context in groundtruth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a groundtruth region, depending on the spatial distribution of the other regions in the groundtruth. Final characterization is given with detection rate/probability score plots, describing the sets of possible interpretations of the localization results, according to a given confidence rate. We present experimentation details along with the results for the symbol localization system of [ 1 ], exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).
机译:在本文中,我们提出了一种用于符号定位系统性能表征的算法。该算法旨在成为一种更“可靠”和“开放”的解决方案来表征性能。为此,它仅利用单点作为定位的结果,并提供了重新考虑系统提供的定位结果的可能性。我们使用关于groundtruth中的上下文信息以及整体本地化结果来检测模棱两可的本地化结果。根据在地面真相中其他区域的空间分布,为定位点和地面真相区域之间的每个匹配计算概率分数。最终特征由检测率/概率分数图给出,描述了根据给定置信度的定位结果的可能解释集。我们利用[1]的符号定位系统的结果,结合建筑平面图和电气图(由200个图像和3861个符号组成)的综合数据集,提供实验细节以及结果。

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