1,721,002 research outputs found
3D modeling by low-cost range cameras: methods and potentialities
Full text linkNowadays the demand of 3D models for the documentation and visualization of objects and environments is continually increasing. However, the traditional 3D modeling techniques and systems (i.e. photogrammetry and laser scanners) can be very expensive and/or onerous, as they often need qualified technicians and specific post-processing phases. Thus, it is important to find new instruments, able to provide low-cost 3D data in real time and in a user-friendly way.
Range cameras seem one of the most promising tools to achieve this goal: they are low-cost 3D scanners, able to easily collect dense point clouds at high frame rate, in a short range (few meters) from the imaged objects.
Such sensors, though, still remain a relatively new 3D measurement technology, not yet exhaustively studied. Thus, it is essential to assess the metric quality of the depth data retrieved by these devices.
This thesis is precisely included in this background: the aim is to evaluate the potentialities of range cameras for geomatic applications and to provide useful indications for their practical use. Therefore the three most popular and/or promising low-cost range cameras, namely the Microsoft Kinect v1, the Micorsoft Kinect v2 and the Occipital Structure Sensor, were firstly characterized from a geomatic point of view in order to assess the metric quality of the depth data retrieved by them.
These investigations showed that such sensors present a depth precision and a depth accuracy in the range of some millimeters to few centimeters, depending both on the operational principle adopted by the single device (Structured Light or Time of Flight) and on the depth itself.
On this basis, two different models were identified for precision and accuracy vs. depth: parabolic for the Structured Light (the Kinect v1 and the Structure Sensor) and linear for Time of Flight (the Kinect v2) sensors, respectively. Then the effectiveness of such accuracy models was demonstrated to be globally compliant with the found precision models for all of the three sensors.
Furthermore, the proposed calibration model was validated for the Structure Sensor: with calibration, the overall RMSE, decreased from 27 to 16 mm.
Finally four case studies were carried out in order to evaluate:
• the performances of the Kinect v2 sensor for monitoring oscillatory motions (relevant for structural and/or industrial monitoring), demonstrating a good ability of the system to detect movements and displacements;
• the integration feasibility of Kinect v2 with a classical stereo system, highlighting the need of an integration of range cameras into 3D classical photogrammetric systems especially to overpass limitations due to acquisition completeness;
• the potentialities of the Structure Sensor for the 3D surveying of indoor environments, showing a more than sufficient accuracy for most applications;
• the potentialities of the Structure Sensor to document archaeological small finds, where metric accuracy seems to be rather good while textured models shows some misalignments.
In conclusion, although the experimental results demonstrated that range cameras have the capability to give good and encouraging results, the performances of traditional 3D modeling techniques in terms of accuracy and precision are still superior and must be preferred when the accuracy requirements are restrictive.
But for a very wide and continuously increasing range of applications, when the required accuracy can be at the level from few millimeters (very close-range) to few centimeters, then range cameras can be a valuable alternative, especially when non expert users are involved. Furthermore, the technology on which these sensors are based is continually evolving, driven also by the new generation of AR/VR reality kits, and certainly also their geometric performances will soon improve
An Open Source Ransac-Based Plug-In for Building Roof Extraction From Lidar Point Clouds
No full textThe Rongorongo tablet C. New technologies and conventional approaches to an undeciphered text
No full textThe Rongorongo script of Rapa Nui (Easter Island) remains undeciphered and its status as language notation is not proven. Only very recently has a full corpus of Rongorongo, with carefully edited texts, appeared, while a consensual inventory of signs remains a desideratum. We report the 3D-modeling of Rongorongo Tablet C, which provides new detail on certain portions of its text, and a new drawing and transcription, complete with paleographic commentary. We also revisit the structure and possible contents of its text - a crucial step towards decipherment. In addition to a previously identified calendar (list of the nights of the moon), Tablet C may include words related to agriculture, well as other lexical lists, perhaps copied for the purpose of learning. We thus combine new technologies and more conventional approaches to offer new insight on an undeciphered inscription
An Open Source Ransac-Based Plug-In for Building Roof Extraction From Lidar Point Clouds
No full text3D Modelling of the Mamari Tablet from the Rongorongo Corpus: Acquisition, Processing Issues, and Outcomes
Full text linkRongorongo is an undeciphered script inscribed on wooden objects from Easter Island (Rapa Nui) in the Pacific Ocean. The existing editions of the inscriptions, and their widespread locations in museums and archives all over the world today constitute a serious obstacle to any objective paleographical assessment. Thus, with a view to a potential decipherment, creating 3D models of the available corpus is of crucial importance, and one of the objectives of the ERC INSCRIBE project, based at the University of Bologna with Professor S. Ferrara as Principal Investigator. In this preliminary work, we present the results of the 3D digitization of the Mamari tablet, one of the longest inscriptions in Rongorongo, housed in the Museum Archives of the Congregazione dei Sacri Cuori di Gesù e Maria in Rome. The tablet is made of wood, with a shiny reflecting surface, characterized by a mainly dark texture. The 3D modelling was carried out with the ScanRider 1.2 laser scanner manufactured by VGER, based on Structured Light technology, taking care to ensure the legibility of each sign while preserving the overall shape of the object as precisely as possible. To overcome the difficulties inherent in the object’s complex fabric, the Mamari tablet was acquired in separate sections (joined together during processing through specific markers), thus managing to optimize the optical parameters of the laser scanner, such as the exposure of the camera and the depth of field of the projector. Furthermore, an evaluation of the 3D reconstruction precision was also carried out, highlighting a precision of few hundredths of millimeters, in agreement with the claimed nominal standard deviation. In addition to the 3D model produced, one of the main results of this endeavor was the definition of a successful method to scan such complex objects, which will be replicated to finalize the complete 3D modelling of the whole Rongorongo corpus of inscriptions
Monitoring seismic hazard with satellite geodesy in Italy: first steps for the integration of GNSS and European Ground Motion Service data
No full textThe potential role of satellite geodesy techniques for seismic hazard assessment, with particular focus on GNSS and InSAR, has been widely investigated in the last decades. These technologies can detect differences in ground velocity of less than one millimeter per year, and could therefore be suitable to highlight the accumulation of tectonic strain. While conventional strain field estimation is performed from a two-dimensional planimetric point of view, a novel approach was introduced by incorporating the independent a-priori tectonic knowledge of the study area to pre-select the directions along which strain accumulation signs should be searched [1, 2]. This method was applied to the earthquakes of Amatrice (2016) and Emilia (2012), analyzing the ground velocity estimated from GNSS station data along two transects of interest. Despite the promising results obtained, the spatial density of GNSS stations was too low to provide a detailed description of the velocity profile along the transects. In this sense, the combination of GNSS and InSAR techniques could greatly improve these analyses. The recent European Ground Motion Service (EGMS) [3] constitutes an ideal dataset to pursue this objective. In the present work, we evaluated the suitability of EGMS data for seismic hazard assessment. To achieve this, we defined transects covering known high seismic hazard regions of Italy, following the scheme outlined in [2], but greatly improving both the spatial resolution along the transects and their inter-distance, leveraging the high spatial density of InSAR measurement points. We evaluated the velocity profile along the transects using the data provided by the EGMS service, and compared the results obtained with velocities measured from GNSS station data, both projecting GNSS data along the satellite line of sight and retrieving displacements eastward and upward considering SAR acquisitions from ascending and descending orbits. Through this comparison we assessed whether the accuracy, the revisiting time and the covered temporal window of EGMS data are sufficient to ensure a correct velocity estimation, and took a first step in the direction of a future integration. Preliminary results obtained in the Irpinia region (Italy) suggested a good performance of EGMS data for the detailed description of the velocity profile and an excellent agreement with GNSS station data
Water reservoirs monitoring through Google Earth Engine: application to Sentinel and Landsat imagery
Full text linkWater reservoirs are subjected to increasing hydrological stresses, therefore continuous and accurate monitoring of these resources is essential to ensure their sustainable management. This work proposes a methodology to remotely monitor the surface extent of water reservoirs through the analysis of satellite multispectral and Synthetic Aperture Radar (SAR) images. In particular, a segmentation strategy was implemented within Google Earth Engine (GEE) to distinguish water bodies from the surrounding land surface and measure their extension, by applying three different approaches to Sentinel-1, Sentinel-2, and Landsat-8 imagery. The first approach is based on the use of the Automatic Water Extraction Index (AWEI) and the self-adaptive Otsu's thresholding method, the second approach is based on the image conversion from RGB (Red-Green-Blue) to HSV (Hue, Saturation, Value) and the use of a parametric threshold, the third approach is based on the use of SAR imagery and an empirically selected threshold. A "static"validation strategy was developed from scratch and standard segmentation metrics were computed to evaluate the accuracy of the three approaches. The average values of the F1 scores on the Sentinel imagery were equal to 0.95, 0.90, and 0.84 for the three approaches, respectively. The same metric on the Landsat imagery was 0.95 for the first approach and 0.93 for the second approach. The best approach, i.e. the AWEI-based method, was then applied to three water bodies in which the effects of the 2022 drought were particularly significant: Sawa lake (Iraq), Poyang lake (China), and Po river (Italy). The results visually highlighted the good performance of the approach in segmenting the water bodies from the surrounding areas
Kinect V2 and rgb stereo cameras integration for depth map enhancement
Full text linkToday range cameras are widespread low-cost sensors based on two different principles of operation: we can distinguish between Structured Light (SL) range cameras (Kinect v1, Structure Sensor, ...) and Time Of Flight (ToF) range cameras (Kinect v2, ...). Both the types are easy to use 3D scanners, able to reconstruct dense point clouds at high frame rate. However the depth maps obtained are often noisy and not enough accurate, therefore it is generally essential to improve their quality. Standard RGB cameras can be a valuable solution to solve such issue. The aim of this paper is therefore to evaluate the integration feasibility of these two different 3D modelling techniques, characterized by complementary features and based on standard low-cost sensors.
For this purpose, a 3D model of a DUPLOTM bricks construction was reconstructed both with the Kinect v2 range camera and by processing one stereo pair acquired with a Canon Eos 1200D DSLR camera. The scale of the photgrammetric model was retrieved from the coordinates measured by Kinect v2. The preliminary results are encouraging and show that the foreseen integration could lead to an higher metric accuracy and a major level of ompleteness with respect to that obtained by using only separated techniques
3D modelling by low-cost range camera: software evaluation and comparison
Full text linkThe aim of this work is to present a comparison among three software applications currently available for the Occipital Structure SensorTM; all these software were developed for collecting 3D models of objects easily and in real-time with this structured light range camera. The SKANECT, itSeez3D and Scanner applications were thus tested: a DUPLOTM bricks construction was scanned with the three applications and the obtained models were compared to the model virtually generated with a standard CAD software, which served as reference.
The results demonstrate that all the software applications are generally characterized by the same level of geometric accuracy, which amounts to very few millimetres. However, the itSeez3D software, which requires a payment of $7 to export each model, represents surely the best solution, both from the point of view of the geometric accuracy and, mostly, at the level of the color restitution. On the other hand, Scanner, which is a free software, presents an accuracy comparable to that of itSeez3D. At the same time, though, the colors are often smoothed and not perfectly overlapped to the corresponding part of the model. Lastly, SKANECT is the software that generates the highest number of points, but it has also some issues with the rendering of the colors
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