@InProceedings{MathieuNicolasDelalandre2009,
author="Mathieu Nicolas Delalandre
and Jean-Yves Ramel
and Ernest Valveny
and Muhammad Muzzamil Luqman",
title="A Performance Characterization Algorithm for Symbol Localization",
booktitle="8th IAPR International Workshop on Graphics Recognition",
year="2009",
publisher="Springer",
pages="3--11",
abstract="In this paper we present an algorithm for performance characterization of symbol localization systems. This algorithm is aimed to be a more {\textquoteleft}{\textquoteleft}reliable{\textquoteright}{\textquoteright} and {\textquoteleft}{\textquoteleft}open{\textquoteright}{\textquoteright} 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).",
optnote="DAG",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1443), last updated on Tue, 25 Feb 2020 12:59:45 +0100"
}