Computer vision and architectural history at eye level: Mixed methods for linking research in the humanities and in information technology (ArchiMediaL)

Information on the history of architecture is embedded in our daily surroundings, in vernacular and heritage buildings and in physical objects, photographs and plans. Historians study these tangible and intangible artefacts and the communities that built and used them. Thus valuable insights are gained into the past and the present as they...

AmsterTime: A Visual Place Recognition Benchmark Dataset for Severe Domain Shift

We introduce AmsterTime: a challenging dataset to benchmark visual place recognition (VPR) in presence of a severe domain shift. AmsterTime offers a collection of 2,500 well-curated images matching the same scene from a street view matched to historical archival image data from Amsterdam city. The image pairs capture the same place with...

Creating a 4D Street View of Amsterdam from Historical Images

The ArchiMediaL project aims to bridge between data science and researches on contemporary and historical built environments by developing state of the art AI algorithms for the automatic linking of available meta-data and image repositories. As a case-study we use the 360,000+ historical images from the Amsterdam Beeldbank database.

Visual Content Analysis and Linked Data for Automatic Enrichment of Architecture-Related Images

Built form dominates the urban space where most people live and work and provides a visual reflection of the local, regional and global esthetical, social, cultural, technological and economic factors and values. Street-view images and historical photo archives are therefore an invaluable source for sociological or historical study; however,...

Sight-seeing in the eyes of deep neural networks

We address the interpretability of convolutional neural networks (CNNs) for predicting a geo-location from an image. In a pilot experiment we classify images of Pittsburgh vs Tokyo and visualize the learned CNN filters. We found that varying the CNN architecture leads to variating in the visualized filters. This calls for further...

Model prediction of subendocardial perfusion of the coronary circulation in the presence of an epicardial coronary artery stenosis

The subendocardium is most vulnerable to ischemia, which is ameliorated by relaxation during diastole and increased coronary pressure. Recent clinical techniques permit the measuring of subendocardial perfusion and it is therefore important to gain insight into how measurements depend on perfusion conditions of the heart. Using data from...