4,930 research outputs found
New instruments and technologies for Cultural Heritage survey: full integration between point clouds and digital photogrammetry
No full textIn the last years the Geomatic Research Group of the Politecnico di Torino faced some new research topics about new instruments for point cloud generation (e.g. Time of Flight cameras) and strong integration between multi-image matching techniques and 3D Point Cloud information in order to solve the ambiguities of the already known matching algorithms. ToF cameras can be a good low cost alternative to LiDAR instruments for the generation of precise and accurate point clouds: up to now the application range is still limited but in a near future they will be able to satisfy the most part of the Cultural Heritage metric survey requirements. On the other hand multi-image matching techniques with a correct and deep integration of the point cloud information can give the correct solution for an "intelligent" survey of the geometric object break-lines, which are the correct starting point for a complete survey. These two research topics are strictly connected to a modern Cultural Heritage 3D survey approach. In this paper after a short analysis of the achieved results, an alternative possible scenario for the development of the metric survey approach inside the wider topic of Cultural Heritage Documentation is reporte
New integration approach of photogrammetric and LIDAR techninques for architectural surveys
No full textAUTOMATIC ROOF OUTLINES RECONSTRUCTION FROM PHOTOGRAMMETRIC DSM
No full textThe 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
Multi-image matching: an "old and new" photogrammetric answer to lidar techniques
No full textOver the last decade, LIDAR techniques have replaced traditional photogrammetric techniques in many applications because of their speed in point cloud generation. However, these laser scanning techniques have non-negligible limits and, for this reason, many researchers have decided to focus on improving the performances of matching technique in order to generate dense point clouds from images.The first tests carried out at the Politecnico di Torino on the first fully-automated multi-image matching commercial software, the ZScan Menci Software, are described in this paper. This instrument was first devised to allow inexperienced users to generate very dense point clouds from image triplets; a customized calibrated bar (0,90 m length) is used for image acquisition. Recently a new version of ZScan has been created in order to elaborate triplets of oriented aerial images and generate DSM: the first results obtained in this way are presented in this paper. Several tests have been performed on the ZScan performances analysing different geometrical configurations (base-to-height ratio) and textures. The evaluation of the geometric precision obtained by this software in point cloud generation may help to understand which performances can be achieved with a fully automated multi-image matching. The evaluation concerns what the most critical aspects of these techniques are and what improvements will be possible in the future. Furthermore a possible new research project is described which has the aim of transferring useful information about breakline location from images to point clouds in order to derive automatically the segmentation algorithms
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