Publications by Rémi Guillaume Petitpierre

London 1890s Ordnance Survey Text Layer

Isabella Di Lenardo, Rémi Guillaume Petitpierre

This dataset contains a sample of 10,000 (3.5%) out of a total of 285,846 text sequences extracted from the 1891–1896 Map of London by the Ordnance Survey (OS). The methodology used for the automated recognition, linking, and sequencing of the text is deta ...

Zenodo2025

Paris and Jerusalem Maps Text Dataset

Isabella Di Lenardo, Rémi Guillaume Petitpierre, Beatrice Vaienti

This dataset contains 82 annotated map samples from diverse historical city maps of Jerusalem and Paris, suitable for map text detection, recognition, and sequencing. ...

Zenodo2025

Revealing the Structure of Land Ownership through the Automatic Vectorisation of Swiss Cadastral Plans

Isabella Di Lenardo, Rémi Guillaume Petitpierre, Lucas Arnaud André Rappo

This paper explores how the dynamics and structure of land ownership can be studied by automating the vectorisation of historical cadastral sources. Our analysis focuses mainly on three cadastres of Lausanne (1722, 1831, 1883). The plans are first georefer ...

2024

A fragment-based approach for computing the long-term visual evolution of historical maps

Frédéric Kaplan, Isabella Di Lenardo, Rémi Guillaume Petitpierre

Cartography, as a strategic technology, is a historical marker. Maps are tightly connected to the cultural construction of the environment. The increasing availability of digital collections of historical map images provides an unprecedented opportunity to ...

Springernature2024

From Automated Bootstrapping to Collaborative Editing: A Framework for 4D City Reconstruction

Didier Louis Dupertuis, Rémi Guillaume Petitpierre, Paul Robert Guhennec, Beatrice Vaienti

We propose a framework for the construction of 4D scientific models for cities of the past. It leverages both the use of computational methods for bootstrapping, and a collaborative interface for visualisation and edition. This permits to continuously enri ...

Zenodo2023

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Frédéric Kaplan, Isabella Di Lenardo, Rémi Guillaume Petitpierre, Beatrice Vaienti

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

2023

An end-to-end pipeline for historical censuses processing

Marion Kramer, Rémi Guillaume Petitpierre, Lucas Arnaud André Rappo

Censuses are structured documents of great value for social and demographic history, which became widespread from the nineteenth century on. However, the plurality of formats and the natural variability of historical data make their extraction arduous and ...

2023

Mapping Memes in the Napoleonic Cadastre: Expanding Frontiers in Memetics

Rémi Guillaume Petitpierre

We develop a practical computational methodology based on memes theory for studying historical cartography. We also propose to investigate the limits of replication fidelity, and the link between memes and their expression, through a case study on the Napo ...

Zenodo2023

Effective annotation for the automatic vectorization of cadastral maps

Rémi Guillaume Petitpierre, Paul Robert Guhennec

The great potential brought by large-scale data in the humanities is still hindered by the time and technicality required for making documents digitally intelligible. Within urban studies, historical cadasters have been hitherto largely under-explored desp ...

OXFORD UNIV PRESS2023

Lausanne Historical Censuses Dataset HTR 35k

Marion Kramer, Rémi Guillaume Petitpierre, Lucas Arnaud André Rappo

This training dataset includes a total of 34,913 manually transcribed text segments. It is dedicated to the handwritten text recognition (HTR) of historical sources, typically tabular records, such as censuses. This dataset is based on a sample of 83 pages ...

Zenodo2023

Recartographier l'espace napoléonien : Une lecture computationnelle du cadastre historique de Lausanne

Isabella Di Lenardo, Rémi Guillaume Petitpierre, Lucas Arnaud André Rappo

Le cadastre napoléonien est une source historique relativement homogène et largement répandue. Cela rend une approche computationnelle particulièrement pertinente. Dans cette étude, nous proposons une méthode de reconnaissance et de vectorisation automatiq ...

2023

1805-1898 Census Records of Lausanne : a Long Digital Dataset for Demographic History

Marion Kramer, Isabella Di Lenardo, Rémi Guillaume Petitpierre, Lucas Arnaud André Rappo

This historical dataset stems from the project of automatic extraction of 72 census records of Lausanne, Switzerland. The complete dataset covers a century of historical demography in Lausanne (1805-1898), which corresponds to 18,831 pages, and nearly 6 mi ...

Zenodo2023

Historical City Maps Semantic Segmentation Dataset

Rémi Guillaume Petitpierre

This dataset includes a total of 635 annotated image patches from historical city maps. It is designed for the semantic segmentation of the maps into 5 semantic classes (building blocks, non-built, water, road network, background frame). 330 patches are ta ...

Zenodo2021

Generic Semantic Segmentation of Historical Maps

Frédéric Kaplan, Isabella Di Lenardo, Rémi Guillaume Petitpierre

Research in automatic map processing is largely focused on homogeneous corpora or even individual maps, leading to inflexible models. Based on two new corpora, the first one centered on maps of Paris and the second one gathering maps of cities from all ove ...

2021