4,948 research outputs found

    Automatic Fracture Orientation Extraction from SfM Point Clouds

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    Geology seeks to understand the history of the Earth and its surface processes through charac- terisation of surface formations and rock units. Chief among the geologists’ tools are rock unit orientation measurements, such as Strike, Dip and Dip Direction. These allow an understanding of both surface and sub-structure on both the local and macro scale. Although the way these techniques can be used to characterise geology are well understood, the need to collect these measurements by hand adds time and expense to the work of the geologist, precludes spontaneity in field work, and coverage is limited to where the geologist can physically reach. In robotics and computer vision, multi-view geometry techniques such as Structure from Motion (SfM) allows reconstructions of objects and scenes using multiple camera views. SfM-based techniques provide advantages over Lidar-type techniques, in areas such as cost and flexibility of use in more varied environmental conditions, while sacrificing extreme levels of fidelity. Regardless of this, camera based techniques such as SfM, have developed to the point where accuracy is possible in the decimetre range. Here is presented a system to automate the measurement of Strike, Dip and Dip Direction using multi-view geometry from video. Rather than deriving measurements using a method applied to the images, such as the Hough Transform, this method takes measurements directly from the software generated point cloud. Point cloud noise is mitigated using a Mahalanobis distance implementation. Significant structure is characterised using a k-nearest neighbour region growing algorithm, and final surface orientations are quantified using the plane, and normal direction cosines

    State of research in automatic as-built modelling

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    This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.aei.2015.01.001Building Information Models (BIMs) are becoming the official standard in the construction industry for encoding, reusing, and exchanging information about structural assets. Automatically generating such representations for existing assets stirs up the interest of various industrial, academic, and governmental parties, as it is expected to have a high economic impact. The purpose of this paper is to provide a general overview of the as-built modelling process, with focus on the geometric modelling side. Relevant works from the Computer Vision, Geometry Processing, and Civil Engineering communities are presented and compared in terms of their potential to lead to automatic as-built modelling.We acknowledge the support of EPSRC Grant NMZJ/114,DARPA UPSIDE Grant A13–0895-S002, NSF CAREER Grant N. 1054127, European Grant Agreements No. 247586 and 334241. We would also like to thank NSERC Canada, Aecon, and SNC-Lavalin for financially supporting some parts of this research

    Multiscale Phenomenology of the Cosmic Web

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    We analyze the structure and connectivity of the distinct morphologies that define the Cosmic Web. With the help of our Multiscale Morphology Filter (MMF), we dissect the matter distribution of a cosmological Λ\LambdaCDM N-body computer simulation into cluster, filaments and walls. The MMF is ideally suited to adress both the anisotropic morphological character of filaments and sheets, as well as the multiscale nature of the hierarchically evolved cosmic matter distribution. The results of our study may be summarized as follows: i).- While all morphologies occupy a roughly well defined range in density, this alone is not sufficient to differentiate between them given their overlap. Environment defined only in terms of density fails to incorporate the intrinsic dynamics of each morphology. This plays an important role in both linear and non linear interactions between haloes. ii).- Most of the mass in the Universe is concentrated in filaments, narrowly followed by clusters. In terms of volume, clusters only represent a minute fraction, and filaments not more than 9%. Walls are relatively inconspicous in terms of mass and volume. iii).- On average, massive clusters are connected to more filaments than low mass clusters. Clusters with M∼1014M \sim 10^{14} M⊙_{\odot} h−1^{-1} have on average two connecting filaments, while clusters with M≥1015M \geq 10^{15} M⊙_{\odot} h−1^{-1} have on average five connecting filaments. iv).- Density profiles indicate that the typical width of filaments is 2\Mpch. Walls have less well defined boundaries with widths between 5-8 Mpc h−1^{-1}. In their interior, filaments have a power-law density profile with slope γ≈−1{\gamma}\approx -1, corresponding to an isothermal density profile.Comment: 28 pages, 22 figures, accepted for publication in MNRAS. For a high-res version see http://www.astro.rug.nl/~weygaert/webmorph_mmf.pd

    On the formation of breakthrough curves tailing during convergent flow tracer tests in three-dimensional heterogeneous aquifers

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    Anomalous transport in advection-dominated convergent flow tracer tests can occurs due to small-scale heterogeneities in aquifer hydraulic properties. These result in fluctuations of the groundwater velocity field and complex connectivity patterns between injection and extraction wells. While detailed characterization of heterogeneity is often not possible in practice, a proper understanding of what fundamental physical mechanisms can give rise to macroscopic behaviors that are measurable is essential for proper upscaling of solute transport processes. We analyze here how heavy-tailed breakthrough curves can arise in radially convergent flow to a well. The permeability fields are three-dimensional multi-Gaussian fields with varying statistical geometry and degrees of heterogeneity. We consider transport of conservative tracers from multiple injection locations by varying distance and angle from the extraction well. Anomalous power law tailing in breakthrough curves is attributed to a variety of features including the initial vertical stratification of the solute that arises due to a flux-weighted injection, the injection distance to the well relative to the depth of the aquifer, and the statistics of the heterogeneity field as defined by the correlation length and variance of the permeability. When certain conditions cooccur for a given injection, such as strong connectivity contrasts between aquifer layers, injection distances comparable to the horizontal heterogeneity integral scales, and large global variances, breakthrough curves tend to scale as a PL with unit slope at late time. These findings offer new insights to understand what physical processes must be understood to develop and choose appropriate upscaling approaches that might reproduce such anomalous transport in heterogeneous advection-dominated systems

    Novel shape indices for vector landscape pattern analysis

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    The formation of an anisotropic landscape is influenced by natural and/or human processes, which can then be inferred on the basis of geometric indices. In this study, two minimal bounding rectangles in consideration of the principles of mechanics (i.e. minimal width bounding (MWB) box and moment bounding (MB) box) were introduced. Based on these boxes, four novel shape indices, namely MBLW (the length-to-width ratio of MB box), PAMBA (area ratio between patch and MB box), PPMBP (perimeter ratio between patch and MB box) and ODI (orientation difference index between MB and MWB boxes), were introduced to capture multiple aspects of landscape features including patch elongation, patch compactness, patch roughness and patch symmetry. Landscape pattern was, thus, quantified by considering both patch directionality and patch shape simultaneously, which is especially suitable for anisotropic landscape analysis. The effectiveness of the new indices were tested with real landscape data consisting of three kinds of saline soil patches (i.e. the elongated shaped slightly saline soil class, the circular or half-moon shaped moderately saline soil, and the large and complex severely saline soil patches). The resulting classification was found to be more accurate and robust than that based on traditional shape complexity indices

    NICP: Dense normal based point cloud registration

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    In this paper we present a novel on-line method to recursively align point clouds. By considering each point together with the local features of the surface (normal and curvature), our method takes advantage of the 3D structure around the points for the determination of the data association between two clouds. The algorithm relies on a least squares formulation of the alignment problem, that minimizes an error metric depending on these surface characteristics. We named the approach Normal Iterative Closest Point (NICP in short). Extensive experiments on publicly available benchmark data show that NICP outperforms other state-of-the-art approaches
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