Piaget: A Probabilistic Inference Approach For Geolocating Historical Buildings

2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA)(2020)

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摘要
We aim to find the geographical coordinates of (geolocate) a large number of old building 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, geolocates 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.
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关键词
Geospatial, Geolocate, Spatial Reasoning, Probabilistic Inference, Belief Propagation
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