Jump to Content

Piaget: A Probabilistic Inference Approach for Geolocating Historical Buildings

Cyrus Shahabi
Feng Han
Raimondas Kiveris
IEEE International Conference on Big Data (2021)

Abstract

We aim to find the geographical location of (geolocate) a large number of old buildings facades extracted from historical photographs. We can acquire the geo-coordinates of some of these facades either through crowdsourcing or exploring their metadata. Using these “seed” buildings and through spatial reasoning within and across the historical pictures, in this paper, we show how we infer the geolocation of the other facades. We propose a probabilistic inference approach that first constructs a graph with facades as nodes and their spatial distances as edges, and then through probabilistic inference on this graph, geolocate the facades. Our experiments show that with 10\% of the building geolocated as seed buildings, we can quite accurately geolocate the rest of the buildings in our dataset.