Abstract:The creation of as-built Building Information Models requires the acquisition of the as-is state of existing buildings. Laser scanners are widely used to achieve this goal since they permit to collect information about object geometry in form of point clouds and provide a large amount of accurate data in a very fast way and with a high level of details. Unfortunately, the scan-to-BIM (Building Information Model) process remains currently largely a manual process which is time consuming and error-prone. In this paper, a semi-automatic approach is presented for the 3D reconstruction of indoors of existing buildings from point clouds. Several segmentations are performed so that point clouds corresponding to grounds, ceilings and walls are extracted. Based on these point clouds, walls and slabs of buildings are reconstructed and described in the IFC format in order to be integrated into BIM software. The assessment of the approach is proposed thanks to two datasets. The evaluation items are the degree of automation, the transferability of the approach and the geometric quality of results of the 3D reconstruction. Additionally, quality indexes are introduced to inspect the results in order to be able to detect potential errors of reconstruction.

Abstract:In the last decade, RGB-D cameras -also called range imaging cameras -have known a permanent evolution. Because of their limited cost and their ability to measure distances at a high frame rate, such sensors are especially appreciated for applications in robotics or computer vision. The Kinect v1 (Microsoft) release in November 2010 promoted the use of RGB-D cameras, so that a second version of the sensor arrived on the market in July 2014. Since it is possible to obtain point clouds of an observed scene with a high frequency, one could imagine applying this type of sensors to answer to the need for 3D acquisition. However, due to the technology involved, some questions have to be considered such as, for example, the suitability and accuracy of RGB-D cameras for close range 3D modeling. In that way, the quality of the acquired data represents a major axis. In this paper, the use of a recent Kinect v2 sensor to reconstruct small objects in three dimensions has been investigated. To achieve this goal, a survey of the sensor characteristics as well as a calibration approach are relevant. After an accuracy assessment of the produced models, the benefits and drawbacks of Kinect v2 compared to the first version of the sensor and then to photogrammetry are discussed.

ABSTRACT:RGB-D cameras, also known as range imaging cameras, are a recent generation of sensors. As they are suitable for measuring distances to objects at high frame rate, such sensors are increasingly used for 3D acquisitions, and more generally for applications in robotics or computer vision. This kind of sensors became popular especially since the Kinect v1 (Microsoft) arrived on the market in November 2010. In July 2014, Windows has released a new sensor, the Kinect for Windows v2 sensor, based on another technology as its first device. However, due to its initial development for video games, the quality assessment of this new device for 3D modelling represents a major investigation axis. In this paper first experiences with Kinect v2 sensor are related, and the ability of close range 3D modelling is investigated. For this purpose, error sources on output data as well as a calibration approach are presented.

Three-dimensional (3D) documentation of heritage buildings has long employed both image-based and range-based techniques. Unmanned aerial vehicles (UAVs) provide a particular advantage for image-based techniques in acquiring aerial views, which are difficult to attain using classical terrestrial-based methods. The technological development of optical sensors and dense matching algorithms also complement existing photogrammetric workflows for the documentation of heritage objects. In this paper, fundamental concepts in photogrammetry and 3D reconstruction based on structure from motion (SfM) will be briefly reviewed. Two case studies were performed using two types of UAVs, one being a state-of-the-art platform dedicated to obtaining close-range images. Comparisons with laser scanning data were performed and several issues regarding the aerial triangulation and dense matching results were assessed. The results show that although the dense matching of these UAV images may generate centimetre-level precision, a further increase in precision is often hampered by the quality of the onboard sensor.

Safeguarding and exploiting Cultural Heritage induce the production of numerous and heterogeneous data. The management of these data is an essential task for the use and the diffusion of the information gathered on the field. Previously, the data handling was a hand-made task done thanks to efficient and experienced methods. Until the growth of computer science, other methods have been carried out for the digital preservation and treatment of Cultural Heritage information. The development of computerized data management systems to store and make use of archaeological datasets is then a significant task nowadays. Especially for sites that have been excavated and worked without computerized means, it is now necessary to put all the data produced onto computer. This allows preservation of the information digitally (in addition with the paper documents) and offers new exploitation possibilities, like the immediate connection of different kinds of data for analyses, or the digital documentation of the site for its improvement. Geographical Information Systems have proved their potentialities in this scope, but they are not always adapted to the management of features at the scale of a particular archaeological site. Therefore this paper aims to present the development of a Virtual Research Environment dedicated to the exploitation of intra-site Cultural Heritage data. The Information System produced is based on open-source software modules dedicated to the Internet, so users can avoid being software driven and can register and consult data from different computers. The system gives the opportunity to do exploratory analyses of the data, especially at spatial and temporal levels. The system is compliant to every kind of Cultural Heritage site and allows management of diverse types of data. Some experimentation has been done on sites managed by the Service of the National Sites and Monuments of Luxembourg.

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