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Point Clouds (point + cloud)
Selected AbstractsAccounting for uncertainty in DEMs from repeat topographic surveys: improved sediment budgetsEARTH SURFACE PROCESSES AND LANDFORMS, Issue 2 2010Joseph M. Wheaton Abstract Repeat topographic surveys are increasingly becoming more affordable, and possible at higher spatial resolutions and over greater spatial extents. Digital elevation models (DEMs) built from such surveys can be used to produce DEM of Difference (DoD) maps and estimate the net change in storage terms for morphological sediment budgets. While these products are extremely useful for monitoring and geomorphic interpretation, data and model uncertainties render them prone to misinterpretation. Two new methods are presented, which allow for more robust and spatially variable estimation of DEM uncertainties and propagate these forward to evaluate the consequences for estimates of geomorphic change. The first relies on a fuzzy inference system to estimate the spatial variability of elevation uncertainty in individual DEMs while the second approach modifies this estimate on the basis of the spatial coherence of erosion and deposition units. Both techniques allow for probabilistic representation of uncertainty on a cell-by-cell basis and thresholding of the sediment budget at a user-specified confidence interval. The application of these new techniques is illustrated with 5 years of high resolution survey data from a 1,km long braided reach of the River Feshie in the Highlands of Scotland. The reach was found to be consistently degradational, with between 570 and 1970,m3 of net erosion per annum, despite the fact that spatially, deposition covered more surface area than erosion. In the two wetter periods with extensive braid-plain inundation, the uncertainty analysis thresholded at a 95% confidence interval resulted in a larger percentage (57% for 2004,2005 and 59% for 2006,2007) of volumetric change being excluded from the budget than the drier years (24% for 2003,2004 and 31% for 2005,2006). For these data, the new uncertainty analysis is generally more conservative volumetrically than a standard spatially-uniform minimum level of detection analysis, but also produces more plausible and physically meaningful results. The tools are packaged in a wizard-driven Matlab software application available for download with this paper, and can be calibrated and extended for application to any topographic point cloud (x,y,z). Copyright © 2009 John Wiley & Sons, Ltd. [source] Recovering Structure from r -Sampled ObjectsCOMPUTER GRAPHICS FORUM, Issue 5 2009O. Aichholzer For a surface in 3-space that is represented by a set S of sample points, we construct a coarse approximating polytope P that uses a subset of S as its vertices and preserves the topology of . In contrast to surface reconstruction we do not use all the sample points, but we try to use as few points as possible. Such a polytope P is useful as a ,seed polytope' for starting an incremental refinement procedure to generate better and better approximations of based on interpolating subdivision surfaces or e.g. Bézier patches. Our algorithm starts from an r -sample S of . Based on S, a set of surface covering balls with maximal radii is calculated such that the topology is retained. From the weighted ,-shape of a proper subset of these highly overlapping surface balls we get the desired polytope. As there is a rather large range for the possible radii for the surface balls, the method can be used to construct triangular surfaces from point clouds in a scalable manner. We also briefly sketch how to combine parts of our algorithm with existing medial axis algorithms for balls, in order to compute stable medial axis approximations with scalable level of detail. [source] Freeform Shape Representations for Efficient Geometry ProcessingCOMPUTER GRAPHICS FORUM, Issue 3 2003Leif Kobbelt The most important concepts for the handling and storage of freeform shapes in geometry processing applications are parametric representations and volumetric representations. Both have their specific advantages and drawbacks. While the algebraic complexity of volumetric representations is independent from the shape complexity, the domain of a parametric representation usually has to have the same structure as the surface itself (which sometimes makes it necessary to update the domain when the surface is modified). On the other hand, the topology of a parametrically defined surface can be controlled explicitly while in a volumetric representation, the surface topology can change accidentally during deformation. A volumetric representation reduces distance queries or inside/outside tests to mere function evaluations but the geodesic neighborhood relation between surface points is difficult to resolve. As a consequence, it seems promising to combine parametric and volumetric representations to effectively exploit both advantages. In this talk, a number of projects are presented and discussed in which such a combination leads to efficient and numerically stable algorithms for the solution of various geometry processing tasks. Applications include global error control for mesh decimation and smoothing, topology control for level-set surfaces, and shape modeling with unstructured point clouds. [source] Rapid Human-Assisted Creation of Bounding Models for Obstacle Avoidance in ConstructionCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 1 2004J. McLaughlin A practical, interactive method for doing so is described here. The method: (1) exploits a human operator's ability to quickly recognize significant objects or clusters of objects in a scene, (2) exploits the operator's ability to acquire sparse range point clouds of the objects quickly, and then (3) renders models, such as planes, boxes, and generalized convex hulls, to be displayed graphically as visual feedback during equipment operation and/or for making proximity calculations in an obstacle detection system. Experiments were performed in which test subjects were asked to model objects of varying complexity and clutter. These models were then compared to control models using a ray-tracing algorithm to determine the operator's ability to create conservative models that are critical to construction operations. To demonstrate the applicability of the modeling method to obstacle avoidance, a scripted motion robot simulation was conducted using an artificial potential formulation that monitors position (closest point on manipulator link to nearest obstacle) as well as velocity (link inertia). Experimental results indicate that bounding models can be created rapidly and with sufficient accuracy for obstacle avoidance with the aid of human intelligence and that human-assisted modeling can be very beneficial for real-time construction equipment control. [source] Automatic appearance-based loop detection from three-dimensional laser data using the normal distributions transformJOURNAL OF FIELD ROBOTICS (FORMERLY JOURNAL OF ROBOTIC SYSTEMS), Issue 11-12 2009Martin Magnusson We propose a new approach to appearance-based loop detection for mobile robots, using three-dimensional (3D) laser scans. Loop detection is an important problem in the simultaneous localization and mapping (SLAM) domain, and, because it can be seen as the problem of recognizing previously visited places, it is an example of the data association problem. Without a flat-floor assumption, two-dimensional laser-based approaches are bound to fail in many cases. Two of the problems with 3D approaches that we address in this paper are how to handle the greatly increased amount of data and how to efficiently obtain invariance to 3D rotations. We present a compact representation of 3D point clouds that is still discriminative enough to detect loop closures without false positives (i.e., detecting loop closure where there is none). A low false-positive rate is very important because wrong data association could have disastrous consequences in a SLAM algorithm. Our approach uses only the appearance of 3D point clouds to detect loops and requires no pose information. We exploit the normal distributions transform surface representation to create feature histograms based on surface orientation and smoothness. The surface shape histograms compress the input data by two to three orders of magnitude. Because of the high compression rate, the histograms can be matched efficiently to compare the appearance of two scans. Rotation invariance is achieved by aligning scans with respect to dominant surface orientations. We also propose to use expectation maximization to fit a gamma mixture model to the output similarity measures in order to automatically determine the threshold that separates scans at loop closures from nonoverlapping ones. We discuss the problem of determining ground truth in the context of loop detection and the difficulties in comparing the results of the few available methods based on range information. Furthermore, we present quantitative performance evaluations using three real-world data sets, one of which is highly self-similar, showing that the proposed method achieves high recall rates (percentage of correctly identified loop closures) at low false-positive rates in environments with different characteristics. © 2009 Wiley Periodicals, Inc. [source] | ||||||||||