ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-3, 257-262, 2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
20 Jul 2012
F. Nex and F. Remondino 3D Optical Metrology (3DOM) unit, Bruno Kessler Foundation (FBK), Trento, Italy
Keywords: Matching, Automation, Aerial, Extraction, Point cloud Abstract. The extraction of geometric and semantic information from image and range data is one of the main research topics. Between the different geomatics products, 3D city models have shown to be a valid instrument for several applications. As a consequence, the interest for automated solutions able to speed up and reduce the costs for 3D model generation is greatly increased. Image matching techniques can nowadays provide for dense and reliable point clouds, practically comparable to LiDAR ones in terms of accuracy and completeness. In this paper a methodology for the geometric reconstruction of roof outlines (eaves, ridges and pitches) from aerial images is presented. The approach keeps in count the fact the usually photogrammetrically derived point clouds and DSMs are more noisy with respect to LiDAR data. A data driven approach is used in order to keep the maximum flexibility and to achieve satisfying reconstructions with different typologies of buildings. Some tests and examples are reported showing the suitability of photogrammetric DSM for this topic and the performances of the developed algorithm in different operative conditions.
Conference paper (PDF, 1399 KB)

Citation: Nex, F. and Remondino, F.: AUTOMATIC ROOF OUTLINES RECONSTRUCTION FROM PHOTOGRAMMETRIC DSM, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-3, 257-262,, 2012.

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