Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

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  • Publication
    Fast extraction of dominant planes in MLS-data of urban areas
    ( 2016)
    Gordon, Marvin
    Many current LIDAR systems generate huge amounts of 3D points, therefore efficient and fast data processing is essential. In urban areas surfaces are often planar and plane patches are an efficient representation for localization purposes. Our approach thus stores the points in a voxel grid and afterwards extracts the dominant plane using RANSAC-based plane fitting. Classical RANSAC-based plane extraction can result in improper planes, especially in the case of steps like curbsides. Different solutions have been presented, but they are computational demanding. We tackle this problem by extending the loss function of the standard RANSAC. This solves the problem in most cases and has nearly no impact on the runtime. We show the improvement using data of an urban environment, which were recorded by an MLS-system.
  • Publication
    A descriptor and voting scheme for fast 3D self-localization in man-made environments
    ( 2016)
    Gordon, Marvin
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    Hebel, Marcus orcid-logo
    ;
    Arens, Michael
    In contrast to the increasing availability of affordable and lightweight 3D sensors, navigation sensors are still big, expensive (IMU), and prone to GPS errors. In view of a lightweight, affordable and robust 3D mapping solution, it is preferable to aim at a low-cost IMU and GPS-less system. Therefore, some capabilities provided by navigation hardware should be replaced by methodical solutions. We present an approach for data-based self-localization in a large-scale 3D model of a man-made environment (e.g., an urban area, an indoor environment), which solves substantial parts of this problem. Our approach uses a rotation invariant descriptor and a 3D voting scheme to determine the own position and orientation within available 3D data of the environment. While our methods can support loop closing during mapping, the main result is the ability for fast and GPS-less initial self-localization.
  • Publication
    Fast and adaptive surface reconstruction from mobile laser scanning data of urban areas
    ( 2015)
    Gordon, Marvin
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    Hebel, Marcus orcid-logo
    ;
    Arens, Michael
    The availability of 3D environment models enables many applications such as visualization, planning or simulation. With the use of current mobile laser scanners it is possible to map large areas in relatively short time. One of the emerging problems is to handle the resulting huge amount of data. We present a fast and adaptive approach to represent connected 3D points by surface patches while keeping fine structures untouched. Our approach results in a reasonable reduction of the data and, on the other hand, it preserves details of the captured scene. At all times during data acquisition and processing, the 3D points are organized in an octree with adaptive cell size for fast handling of the data. Cells of the octree are filled with points and split into subcells, if the points do not lie on one plane or are not evenly distributed on the plane. In order to generate a polygon model, each octree cell and its corresponding plane are intersected. As a main result, our approach allows the online generation of an expandable 3D model of controllable granularity. Experiments have been carried out using a sensor vehicle with two laser scanners at an urban test site. The results of the experiments show that the demanded compromise between data reduction and preservation of details can be reached.
  • Publication
    Ad hoc model generation using multiscale LIDAR data from a geospatial database
    ( 2015)
    Gordon, Marvin
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    Borgmann, Björn
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    Gehrung, Joachim
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    Hebel, Marcus orcid-logo
    ;
    Arens, Michael
    Due to the spread of economically priced laser scanning technology nowadays, especially in the field of topographic surveying and mapping, ever-growing amounts of data need to be handled. Depending on the requirements of the specific application, airborne, mobile or terrestrial laser scanners are commonly used. Since visualizing this flood of data is not feasible with classical approaches like raw point cloud rendering, real time decision making requires sophisticated solutions. In addition, the efficient storage and recovery of 3D measurements is a challenging task. Therefore we propose an approach for the intelligent storage of 3D point clouds using a spatial database. For a given region of interest, the database is queried for the data available. All resulting point clouds are fused in a model generation process, utilizing the fact that low density airborne measurements could be used to supplement higher density mobile or terrestrial laser scans. The octree based modeling approach divides and subdivides the world into cells of varying size and fits one plane per cell, once a specified amount of points is present. The resulting model exceeds the completeness and precision of every single data source and enables for real time visualization. This is especially supported by data compression ratios of about 90%.
  • Publication
    Automatic change detection using mobile laser scanning
    ( 2014)
    Hebel, Marcus orcid-logo
    ;
    Hammer, Marcus
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    Gordon, Marvin
    ;
    Arens, Michael
    Automatic change detection in 3D environments requires the comparison of multi-temporal data. By comparing current data with past data of the same area, changes can be automatically detected and identified. Volumetric changes in the scene hint at suspicious activities like the movement of military vehicles, the application of camouflage nets, or the placement of IEDs, etc. In contrast to broad research activities in remote sensing with optical cameras, this paper addresses the topic using 3D data acquired by mobile laser scanning (MLS). We present a framework for immediate comparison of current MLS data to given 3D reference data. Our method extends the concept of occupancy grids known from robot mapping, which incorporates the sensor positions in the processing of the 3D point clouds. This allows extracting the information that is included in the data acquisition geometry. For each single range measurement, it becomes apparent that an object reflects laser pulses in the measured range distance, i.e., space is occupied at that 3D position. In addition, it is obvious that space is empty along the line of sight between sensor and the reflecting object. Everywhere else, the occupancy of space remains unknown. This approach handles occlusions and changes implicitly, such that the latter are identifiable by conflicts of empty space and occupied space. The presented concept of change detection has been successfully validated in experiments with recorded MLS data streams. Results are shown for test sites at which MLS data were acquired at different time intervals.
  • Publication
    Calibration of a multi-beam laser system by using a TLS-generated reference
    ( 2013)
    Gordon, Marvin
    ;
    Meidow, Jochen orcid-logo
    Rotating multi-beam LIDARs mounted on moving platforms have become very successful for many applications such as autonomous navigation, obstacle avoidance or mobile mapping. To obtain accurate point coordinates, a precise calibration of such a LIDAR system is required. For the determination of the corresponding parameters we propose a calibration scheme which exploits the information of 3D reference point clouds captured by a terrestrial laser scanning (TLS) device. It is assumed that the accuracy of this point clouds is considerably higher than that from the multi-beam LIDAR and that the data represent faces of man-made objects at different distances. After extracting planes in the reference data sets, the point-plane-incidences of the measured points and the reference planes are used to formulate the implicit constraints. We inspect the Velodyne HDL-64E S2 system as the best-known representative for this kind of sensor system. The usability and feasibility of the calibration procedure is demonstrated with real data sets representing building faces (walls, roof planes and ground). Beside the improvement of the point accuracy by considering the calibration results, we test the significance of the parameters related to the sensor model and consider the uncertainty of measurements w.r.t. the measured distances. The Velodyne returns two kinds of measurements-distances and encoder angles. To account for this, we perform a variance component estimation to obtain realistic standard deviations for the observations.