Automatic image analysis and real estate

The year of construction (age) of a property, as well as the period of construction has an essential influence on the structure and the value of a building. Current automatic classification models of properties apply hedonic approaches that are mostly based on location (address). An additional automatic classification based on the age and/or period of construction in real estate valuations is still missing.Driven by this observation, the aim is to undertake fundamental research in the jointly interdisciplinary fields of image analysis and real estate evaluation in order to develop novel automatic visual analysis methods for the estimation of age/period of construction of buildings. We employ photographs that show the face of family houses to predict the period of construction and the coarse age as well as the region the building resides in.Image analysis has a long research tradition and is today applied in many different domains. In the domain of real estates, however, the major focus of image analysis lies in the area of satellite image analysis for the classification of land cover. Detained building information cannot be extracted from satellite images. In contrast to other existing approaches, we employ unconstrained photographs of buildings (e.g. by brokers, owners and real estate experts) as an input to visually extract information about the building. For this purpose our business partner provides a large database of real estate valuations. These valuations contain detailed object property descriptions such as year of construction, condition, amenities, address, value, etc., as well as several images per object in different views.In our presentation we will first give a literature overview bout existing papers which are in context real estate (building) an image analysis. In the following we would like to present first results from our research. Therefore we apply the method from (Lee, Maisonneuve, Crandall, Efros, & Sivic, 2015) and our first results are satisfactory.Source: Lee, S., Maisonneuve, N., Crandall, D., Efros, A. A., & Sivic, J. (2015, April 24). Linking Past to Present: Discovering Style in Two Centuries of Architecture. IEEE International Conference on Computational Photography.