TitleAutomatic Prediction of Building Age from Photographs
Publication TypeConference Paper
Year of Publication2018
AuthorsZeppelzauer, M., M. Despotovic, M. Sakeena, D. Koch, and M. Döller
Conference NameProceedings of the 2018 ACM on International Conference on Multimedia Retrieval
Pages126–134
PublisherACM
Conference LocationNew York, NY, USA
ISBN Number978-1-4503-5046-4
Keywordsbuilding age estimation, Building Analysis, Content-based image retrieval, Deep Learning, image classification, visual pattern extraction
AbstractWe present a first method for the automated age estimation of buildings from unconstrained photographs. To this end, we propose a two-stage approach that firstly learns characteristic visual patterns for different building epochs at patch-level and then globally aggregates patch-level age estimates over the building. We compile evaluation datasets from different sources and perform an detailed evaluation of our approach, its sensitivity to parameters, and the capabilities of the employed deep networks to learn characteristic visual age-related patterns. Results show that our approach is able to estimate building age at a surprisingly high level that even outperforms human evaluators and thereby sets a new performance baseline. This work represents a first step towards the automated assessment of building parameters for automated price prediction.
URLhttps://arxiv.org/abs/1804.02205
DOI10.1145/3206025.3206060
Refereed DesignationRefereed