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    Data from: ICDAR 2021 Competition on Historical Map Segmentation — Dataset

    • data.niaid.nih.gov
    • zenodo.org
    Updated May 30, 2021
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    Chazalon, Joseph; Carlinet, Edwin; Chen, Yizi; Perret, Julien; Duménieu, Bertrand; Mallet, Clément; Géraud, Thierry (2021). ICDAR 2021 Competition on Historical Map Segmentation — Dataset [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_4817661
    Explore at:
    Dataset updated
    May 30, 2021
    Dataset provided by
    EPITA Research and Development Laboratory
    Univ. Gustave Eiffel, IGN-ENSG, LaSTIG
    LaDéHiS, CRH, EHESS
    Authors
    Chazalon, Joseph; Carlinet, Edwin; Chen, Yizi; Perret, Julien; Duménieu, Bertrand; Mallet, Clément; Géraud, Thierry
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    ICDAR 2021 Competition on Historical Map Segmentation — Dataset

    This is the dataset of the ICDAR 2021 Competition on Historical Map Segmentation (“MapSeg”). This competition ran from November 2020 to April 2021. Evaluation tools are freely available but distributed separately.

    Official competition website: https://icdar21-mapseg.github.io/

    The competition report can be cited as:

    Joseph Chazalon, Edwin Carlinet, Yizi Chen, Julien Perret, Bertrand Duménieu, Clément Mallet, Thierry Géraud, Vincent Nguyen, Nam Nguyen, Josef Baloun, Ladislav Lenc, and Pavel Král, "ICDAR 2021 Competition on Historical Map Segmentation", in Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR'21), September 5-10, 2021, Lausanne, Switzerland.

    BibTeX entry:

    @InProceedings{chazalon.21.icdar.mapseg, author = {Joseph Chazalon and Edwin Carlinet and Yizi Chen and Julien Perret and Bertrand Duménieu and Clément Mallet and Thierry Géraud and Vincent Nguyen and Nam Nguyen and Josef Baloun and Ladislav Lenc and and Pavel Král}, title = {ICDAR 2021 Competition on Historical Map Segmentation}, booktitle = {Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR'21)}, year = {2021}, address = {Lausanne, Switzerland}, }

    We thank the City of Paris for granting us with the permission to use and reproduce the atlases used in this work.

    The images of this dataset are extracted from a series of 9 atlases of the City of Paris produced between 1894 and 1937 by the Map Service (“Service du plan”) of the City of Paris, France, for the purpose of urban management and planning. For each year, a set of approximately 20 sheets forms a tiled view of the city, drawn at 1/5000 scale using trigonometric triangulation.

    Sample citation of original documents:

    Atlas municipal des vingt arrondissements de Paris. 1894, 1895, 1898, 1905, 1909, 1912, 1925, 1929, and 1937. Bibliothèque de l’Hôtel de Ville. City of Paris. France.

    Motivation

    This competition aims as encouraging research in the digitization of historical maps. In order to be usable in historical studies, information contained in such images need to be extracted. The general pipeline involves multiples stages; we list some essential ones here:

    segment map content: locate the area of the image which contains map content;

    extract map object from different layers: detect objects like roads, buildings, building blocks, rivers, etc. to create geometric data;

    georeference the map: by detecting objects at known geographic coordinate, compute the transformation to turn geometric objects into geographic ones (which can be overlaid on current maps).

    Task overview

    Task 1: Detection of building blocks

    Task 2: Segmentation of map content within map sheets

    Task 3: Localization of graticule lines intersections

    Please refer to the enclosed README.md file or to the official website for the description of tasks and file formats.

    Evaluation metrics and tools

    Evaluation metrics are described in the competition report and tools are available at https://github.com/icdar21-mapseg/icdar21-mapseg-eval and should also be archived using Zenodo.

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Click to copy link
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Cite
Chazalon, Joseph; Carlinet, Edwin; Chen, Yizi; Perret, Julien; Duménieu, Bertrand; Mallet, Clément; Géraud, Thierry (2021). ICDAR 2021 Competition on Historical Map Segmentation — Dataset [Dataset]. https://data.niaid.nih.gov/resources?id=ZENODO_4817661

Data from: ICDAR 2021 Competition on Historical Map Segmentation — Dataset

Related Article
Explore at:
Dataset updated
May 30, 2021
Dataset provided by
EPITA Research and Development Laboratory
Univ. Gustave Eiffel, IGN-ENSG, LaSTIG
LaDéHiS, CRH, EHESS
Authors
Chazalon, Joseph; Carlinet, Edwin; Chen, Yizi; Perret, Julien; Duménieu, Bertrand; Mallet, Clément; Géraud, Thierry
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

ICDAR 2021 Competition on Historical Map Segmentation — Dataset

This is the dataset of the ICDAR 2021 Competition on Historical Map Segmentation (“MapSeg”). This competition ran from November 2020 to April 2021. Evaluation tools are freely available but distributed separately.

Official competition website: https://icdar21-mapseg.github.io/

The competition report can be cited as:

Joseph Chazalon, Edwin Carlinet, Yizi Chen, Julien Perret, Bertrand Duménieu, Clément Mallet, Thierry Géraud, Vincent Nguyen, Nam Nguyen, Josef Baloun, Ladislav Lenc, and Pavel Král, "ICDAR 2021 Competition on Historical Map Segmentation", in Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR'21), September 5-10, 2021, Lausanne, Switzerland.

BibTeX entry:

@InProceedings{chazalon.21.icdar.mapseg, author = {Joseph Chazalon and Edwin Carlinet and Yizi Chen and Julien Perret and Bertrand Duménieu and Clément Mallet and Thierry Géraud and Vincent Nguyen and Nam Nguyen and Josef Baloun and Ladislav Lenc and and Pavel Král}, title = {ICDAR 2021 Competition on Historical Map Segmentation}, booktitle = {Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR'21)}, year = {2021}, address = {Lausanne, Switzerland}, }

We thank the City of Paris for granting us with the permission to use and reproduce the atlases used in this work.

The images of this dataset are extracted from a series of 9 atlases of the City of Paris produced between 1894 and 1937 by the Map Service (“Service du plan”) of the City of Paris, France, for the purpose of urban management and planning. For each year, a set of approximately 20 sheets forms a tiled view of the city, drawn at 1/5000 scale using trigonometric triangulation.

Sample citation of original documents:

Atlas municipal des vingt arrondissements de Paris. 1894, 1895, 1898, 1905, 1909, 1912, 1925, 1929, and 1937. Bibliothèque de l’Hôtel de Ville. City of Paris. France.

Motivation

This competition aims as encouraging research in the digitization of historical maps. In order to be usable in historical studies, information contained in such images need to be extracted. The general pipeline involves multiples stages; we list some essential ones here:

segment map content: locate the area of the image which contains map content;

extract map object from different layers: detect objects like roads, buildings, building blocks, rivers, etc. to create geometric data;

georeference the map: by detecting objects at known geographic coordinate, compute the transformation to turn geometric objects into geographic ones (which can be overlaid on current maps).

Task overview

Task 1: Detection of building blocks

Task 2: Segmentation of map content within map sheets

Task 3: Localization of graticule lines intersections

Please refer to the enclosed README.md file or to the official website for the description of tasks and file formats.

Evaluation metrics and tools

Evaluation metrics are described in the competition report and tools are available at https://github.com/icdar21-mapseg/icdar21-mapseg-eval and should also be archived using Zenodo.

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