In recent years, advances in computer hardware, graphics rendering algorithms and computer vision have enabled the utilization of 3D building reconstructions in the fields of archeological structure restoration and urban planning. This paper deals with the reconstruction of realistic 3D models of buildings façades, in the urban environment for cultural heritage. The proposed approach is an extension of our previous work in this research topic, which introduced a methodology for accurate 3D realistic façade reconstruction by defining and exploiting a relation between stereoscopic image and tacheometry data. In this work, we re-purpose well known deep neural network architectures in the fields of image segmentation and single image depth prediction, for the tasks of façade structural element detection, depth point-cloud generation and protrusion estimation, with the goal of alleviating drawbacks in our previous design, resulting in a more light-weight, robust, flexible and cost-effective design.
3D building façade reconstruction has become a very popular topic in various applications related to restoration and preservation of architectural structures as well as urban planning. This paper deals with the reconstruction of realistic 3D models of buildings façades, in the urban environment for cultural heritage. We present an approach that enables the relation of stereoscopic images with tacheometry data. The proposed multimodal fusing scheme results in an accurate 3D realistic façade reconstruction and provides a fast and low cost solution. In the first stage of the proposed approach a 2D skeleton of the building is extracted from the viewed scene using Active Contour and Hough line extraction. The next stage of our method utilizes depth information, extracted from a stereoscopic layout, to infer the structural details of inner façade structures, such as windows or doors. In the final stage, the structural information extracted from the image data is integrated with georeferenced point datasets. The final output of our method is a georeferenced 3D model of the structure's façade, which can be further refined with the use of image-driven texture information.
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