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August 30, 2012

A Performance Characterization Algorithm for Symbol Localization

  • September 27, 2022 till September 27, 2022
  • Main Lecture Room

In this talk, we will 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 ground truth, and overall localization results, to detect the ambiguous localization results. A probability score is computed for each matching between a localization point and a ground truth region, depending on the spatial distribution of the other regions in the ground truth. 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 os symbol localization systems, exploiting a synthetic dataset of architectural floorplans and electrical diagrams (composed of 200 images and 3861 symbols).

Talk slides in pdf [~2,7MB]

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