980 resultados para Point cloud processing
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The classification of airborne lidar data is a relevant task in different disciplines. The information about the geometry and the full waveform can be used in order to classify the 3D point cloud. In Wadden Sea areas the classification of lidar data is of main interest for the scientific monitoring of coastal morphology and habitats, but it becomes a challenging task due to flat areas with hardly any discriminative objects. For the classification we combine a Conditional Random Fields framework with a Random Forests approach. By classifying in this way, we benefit from the consideration of context on the one hand and from the opportunity to utilise a high number of classification features on the other hand. We investigate the relevance of different features for the lidar points in coastal areas as well as for the interaction of neighbouring points.
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Babassu and camelina oils have been transesterified with methanol by the classical homogeneous basic catalysis method with good yields. The babassu fatty acid methyl ester (FAME) has been subjected to fractional distillation at vacuum, and the low boiling point fraction has been blended with two types of fossil kerosene, a straight-run atmospheric distillation cut (hydrotreated) and a commercial Jet-A1. The camelina FAME has been blended with the fossil kerosene without previous distillation. The blends of babassu biokerosene and Jet-A1 have met some of the specifications selected for study of the ASTM D1655 standard: smoke point, density, flash point, cloud point, kinematic viscosity, oxidative stability and lower heating value. On the other hand, the blends of babassu biokerosene and atmospheric distillation cut only have met the density parameter and the oxidative stability. The blends of camelina FAME and atmospheric distillation cut have met the following specifications: density, kinematic viscosity at −20 °C, and lower heating value. With these preliminary results, it can be concluded that it would be feasible to blend babassu and camelina biokerosenes prepared in this way with commercial Jet-A1 up to 10 vol % of the former, if these blends prove to accomplish all the ASTM D1655-09 standards.
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El artículo aborda el problema del encaje de diversas imágenes de una misma escena capturadas por escáner 3d para generar un único modelo tridimensional. Para ello se utilizaron algoritmos genéticos. ABSTRACT: This work introduces a solution based on genetic algorithms to find the overlapping area between two point cloud captures obtained from a three-dimensional scanner. Considering three translation coordinates and three rotation angles, the genetic algorithm evaluates the matching points in the overlapping area between the two captures given that transformation. Genetic simulated annealing is used to improve the accuracy of the results obtained by the genetic algorithm.
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The monkey anterior intraparietal area (AIP) encodes visual information about three-dimensional object shape that is used to shape the hand for grasping. In robotics a similar role has been played by modules that fit point cloud data to the superquadric family of shapes and its various extensions. We developed a model of shape tuning in AIP based on cosine tuning to superquadric parameters. However, the model did not fit the data well, and we also found that it was difficult to accurately reproduce these parameters using neural networks with the appropriate inputs (modelled on the caudal intraparietal area, CIP). The latter difficulty was related to the fact that there are large discontinuities in the superquadric parameters between very similar shapes. To address these limitations we adopted an alternative shape parameterization based on an Isomap nonlinear dimension reduction. The Isomap was built using gradients and curvatures of object surface depth. This alternative parameterization was low-dimensional (like superquadrics), but data-driven (similar to an alternative clustering approach that is also sometimes used in robotics) and lacked large discontinuities. Isomaps with 16 or more dimensions reproduced the AIP data fairly well. Moreover, we found that the Isomap parameters could be approximated from CIP-like input much more accurately than the superquadric parameters. We conclude that Isomaps, or perhaps alternative dimension reductions of CIP signals, provide a promising model of AIP tuning. We have now started to integrate our model with a robot hand, to explore the efficacy of Isomap shape reductions in grasp planning. Future work will consider dynamics of spike responses and integration with related visual and motor area models.
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Nowadays, the use of RGB-D sensors have focused a lot of research in computer vision and robotics. These kinds of sensors, like Kinect, allow to obtain 3D data together with color information. However, their working range is limited to less than 10 meters, making them useless in some robotics applications, like outdoor mapping. In these environments, 3D lasers, working in ranges of 20-80 meters, are better. But 3D lasers do not usually provide color information. A simple 2D camera can be used to provide color information to the point cloud, but a calibration process between camera and laser must be done. In this paper we present a portable calibration system to calibrate any traditional camera with a 3D laser in order to assign color information to the 3D points obtained. Thus, we can use laser precision and simultaneously make use of color information. Unlike other techniques that make use of a three-dimensional body of known dimensions in the calibration process, this system is highly portable because it makes use of small catadioptrics that can be placed in a simple manner in the environment. We use our calibration system in a 3D mapping system, including Simultaneous Location and Mapping (SLAM), in order to get a 3D colored map which can be used in different tasks. We show that an additional problem arises: 2D cameras information is different when lighting conditions change. So when we merge 3D point clouds from two different views, several points in a given neighborhood could have different color information. A new method for color fusion is presented, obtaining correct colored maps. The system will be tested by applying it to 3D reconstruction.
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Paper submitted to the 43rd International Symposium on Robotics (ISR2012), Taipei, Taiwan, Aug. 29-31, 2012.
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Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.
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Disponible en Github: https://github.com/adririquelme/DSE
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In this thesis a methodology for representing 3D subjects and their deformations in adverse situations is studied. The study is focused in providing methods based on registration techniques to improve the data in situations where the sensor is working in the limit of its sensitivity. In order to do this, it is proposed two methods to overcome the problems which can difficult the process in these conditions. First a rigid registration based on model registration is presented, where the model of 3D planar markers is used. This model is estimated using a proposed method which improves its quality by taking into account prior knowledge of the marker. To study the deformations, it is proposed a framework to combine multiple spaces in a non-rigid registration technique. This proposal improves the quality of the alignment with a more robust matching process that makes use of all available input data. Moreover, this framework allows the registration of multiple spaces simultaneously providing a more general technique. Concretely, it is instantiated using colour and location in the matching process for 3D location registration.
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Underwater video transects have become a common tool for quantitative analysis of the seafloor. However a major difficulty remains in the accurate determination of the area surveyed as underwater navigation can be unreliable and image scaling does not always compensate for distortions due to perspective and topography. Depending on the camera set-up and available instruments, different methods of surface measurement are applied, which make it difficult to compare data obtained by different vehicles. 3-D modelling of the seafloor based on 2-D video data and a reference scale can be used to compute subtransect dimensions. Focussing on the length of the subtransect, the data obtained from 3-D models created with the software PhotoModeler Scanner are compared with those determined from underwater acoustic positioning (ultra short baseline, USBL) and bottom tracking (Doppler velocity log, DVL). 3-D model building and scaling was successfully conducted on all three tested set-ups and the distortion of the reference scales due to substrate roughness was identified as the main source of imprecision. Acoustic positioning was generally inaccurate and bottom tracking unreliable on rough terrain. Subtransect lengths assessed with PhotoModeler were on average 20% longer than those derived from acoustic positioning due to the higher spatial resolution and the inclusion of slope. On a high relief wall bottom tracking and 3-D modelling yielded similar results. At present, 3-D modelling is the most powerful, albeit the most time-consuming, method for accurate determination of video subtransect dimensions.
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We present a video-based system which interactively captures the geometry of a 3D object in the form of a point cloud, then recognizes and registers known objects in this point cloud in a matter of seconds (fig. 1). In order to achieve interactive speed, we exploit both efficient inference algorithms and parallel computation, often on a GPU. The system can be broken down into two distinct phases: geometry capture, and object inference. We now discuss these in further detail. © 2011 IEEE.
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The first long-term aerosol sampling and chemical characterization results from measurements at the Cape Verde Atmospheric Observatory (CVAO) on the island of São Vicente are presented and are discussed with respect to air mass origin and seasonal trends. In total 671 samples were collected using a high-volume PM10 sampler on quartz fiber filters from January 2007 to December 2011. The samples were analyzed for their aerosol chemical composition, including their ionic and organic constituents. Back trajectory analyses showed that the aerosol at CVAO was strongly influenced by emissions from Europe and Africa, with the latter often responsible for high mineral dust loading. Sea salt and mineral dust dominated the aerosol mass and made up in total about 80% of the aerosol mass. The 5-year PM10 mean was 47.1 ± 55.5 µg/m**2, while the mineral dust and sea salt means were 27.9 ± 48.7 and 11.1 ± 5.5 µg/m**2, respectively. Non-sea-salt (nss) sulfate made up 62% of the total sulfate and originated from both long-range transport from Africa or Europe and marine sources. Strong seasonal variation was observed for the aerosol components. While nitrate showed no clear seasonal variation with an annual mean of 1.1 ± 0.6 µg/m**3, the aerosol mass, OC (organic carbon) and EC (elemental carbon), showed strong winter maxima due to strong influence of African air mass inflow. Additionally during summer, elevated concentrations of OM were observed originating from marine emissions. A summer maximum was observed for non-sea-salt sulfate and was connected to periods when air mass inflow was predominantly of marine origin, indicating that marine biogenic emissions were a significant source. Ammonium showed a distinct maximum in spring and coincided with ocean surface water chlorophyll a concentrations. Good correlations were also observed between nss-sulfate and oxalate during the summer and winter seasons, indicating a likely photochemical in-cloud processing of the marine and anthropogenic precursors of these species. High temporal variability was observed in both chloride and bromide depletion, differing significantly within the seasons, air mass history and Saharan dust concentration. Chloride (bromide) depletion varied from 8.8 ± 8.5% (62 ± 42%) in Saharan-dust-dominated air mass to 30 ± 12% (87 ± 11%) in polluted Europe air masses. During summer, bromide depletion often reached 100% in marine as well as in polluted continental samples. In addition to the influence of the aerosol acidic components, photochemistry was one of the main drivers of halogenide depletion during the summer; while during dust events, displacement reaction with nitric acid was found to be the dominant mechanism. Positive matrix factorization (PMF) analysis identified three major aerosol sources: sea salt, aged sea salt and long-range transport. The ionic budget was dominated by the first two of these factors, while the long-range transport factor could only account for about 14% of the total observed ionic mass.
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In recent years, depth cameras have been widely utilized in camera tracking for augmented and mixed reality. Many of the studies focus on the methods that generate the reference model simultaneously with the tracking and allow operation in unprepared environments. However, methods that rely on predefined CAD models have their advantages. In such methods, the measurement errors are not accumulated to the model, they are tolerant to inaccurate initialization, and the tracking is always performed directly in reference model's coordinate system. In this paper, we present a method for tracking a depth camera with existing CAD models and the Iterative Closest Point (ICP) algorithm. In our approach, we render the CAD model using the latest pose estimate and construct a point cloud from the corresponding depth map. We construct another point cloud from currently captured depth frame, and find the incremental change in the camera pose by aligning the point clouds. We utilize a GPGPU-based implementation of the ICP which efficiently uses all the depth data in the process. The method runs in real-time, it is robust for outliers, and it does not require any preprocessing of the CAD models. We evaluated the approach using the Kinect depth sensor, and compared the results to a 2D edge-based method, to a depth-based SLAM method, and to the ground truth. The results show that the approach is more stable compared to the edge-based method and it suffers less from drift compared to the depth-based SLAM.
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Laser scanning is a terrestrial laser-imaging system that creates highly accurate three-dimensional images of objects for use in standard computer-aided design software packages. This report describes results of a pilot study to investigate the use of laser scanning for transportation applications in Iowa. After an initial training period on the use of the scanner and Cyclone software, pilot tests were performed on the following projects: intersection and railroad bridge for training purposes; section of highway to determine elevation accuracy and pair of bridges to determine level of detail that can be captured; new concrete pavement to determine smoothness; bridge beams to determine camber for deck-loading calculations; stockpile to determine volume; and borrow pit to determine volume. Results show that it is possible to obtain 2-6 mm precision with the laser scanner as claimed by the manufacturer compared to approximately one-inch precision with aerial photogrammetry using a helicopter. A cost comparison between helicopter photogrammetry and laser scanning showed that laser scanning was approximately 30 percent higher in cost depending on assumptions. Laser scanning can become more competitive to helicopter photogrammetry by elevating the scanner on a boom truck and capturing both sides of a divided roadway at the same time. Two- and three-dimensional drawings were created in MicroStation for one of the scanned highway bridges. It was demonstrated that it is possible to create such drawings within the accuracy of this technology. It was discovered that a significant amount of time is necessary to convert point cloud images into drawings. As this technology matures, this task should become less time consuming. It appears that laser scanning technology does indeed have a place in the Iowa Department of Transportation design and construction toolbox. Based on results from this study, laser scanning can be used cost effectively for preliminary surveys to develop TIN meshes of roadway surfaces. It also appears that this technique can be used quite effectively to measure bridge beam camber in a safer and quicker fashion compared to conventional approaches. Volume calculations are also possible using laser scanning. It seems that measuring quantities of rock could be an area where this technology would be quite beneficial since accuracy is more important with this material compared to soil. Other applications for laser scanning could include developing as-built drawings of historical structures such as the bridges of Madison County. This technology could also be useful where safety is a concern such as accurately measuring the surface of a highway active with traffic or scanning the underside of a bridge damaged by a truck. It is recommended that the Iowa Department of Transportation initially rent the scanner when it is needed and purchase the software. With time, it may be cost justifiable to purchase the scanner as well. Laser scanning consultants can be hired as well but at a higher cost.
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Surface flow types (SFT) are advocated as ecologically relevant hydraulic units, often mapped visually from the bankside to characterise rapidly the physical habitat of rivers. SFT mapping is simple, non-invasive and cost-efficient. However, it is also qualitative, subjective and plagued by difficulties in recording accurately the spatial extent of SFT units. Quantitative validation of the underlying physical habitat parameters is often lacking, and does not consistently differentiate between SFTs. Here, we investigate explicitly the accuracy, reliability and statistical separability of traditionally mapped SFTs as indicators of physical habitat, using independent, hydraulic and topographic data collected during three surveys of a c. 50m reach of the River Arrow, Warwickshire, England. We also explore the potential of a novel remote sensing approach, comprising a small unmanned aerial system (sUAS) and Structure-from-Motion photogrammetry (SfM), as an alternative method of physical habitat characterisation. Our key findings indicate that SFT mapping accuracy is highly variable, with overall mapping accuracy not exceeding 74%. Results from analysis of similarity (ANOSIM) tests found that strong differences did not exist between all SFT pairs. This leads us to question the suitability of SFTs for characterising physical habitat for river science and management applications. In contrast, the sUAS-SfM approach provided high resolution, spatially continuous, spatially explicit, quantitative measurements of water depth and point cloud roughness at the microscale (spatial scales ≤1m). Such data are acquired rapidly, inexpensively, and provide new opportunities for examining the heterogeneity of physical habitat over a range of spatial and temporal scales. Whilst continued refinement of the sUAS-SfM approach is required, we propose that this method offers an opportunity to move away from broad, mesoscale classifications of physical habitat (spatial scales 10-100m), and towards continuous, quantitative measurements of the continuum of hydraulic and geomorphic conditions which actually exists at the microscale.