In recent years, 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited, because most models are pure representations with no or little associated semantics. In this paper, we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Furthermore, a Markov Random Field is used to model the temperature distribution of detected windows to further label the windows as either open, closed or damaged.
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Demisse et al. (2013) studied this question.
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