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Peter Teunissen - One of the best experts on this subject based on the ideXlab platform.

  • scanning geometry Influencing Factor on the quality of terrestrial laser scanning points
    Isprs Journal of Photogrammetry and Remote Sensing, 2011
    Co-Authors: Sylvie Soudarissanane, Roderik Lindenbergh, Massimo Menenti, Peter Teunissen
    Abstract:

    A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major Factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality.

  • Scanning geometry: Influencing Factor on the quality of terrestrial laser scanning points
    ISPRS Journal of Photogrammetry and Remote Sensing, 2011
    Co-Authors: Sylvie Soudarissanane, Roderik Lindenbergh, Massimo Menenti, Peter Teunissen
    Abstract:

    A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major Factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality. © 2011 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Sylvie Soudarissanane - One of the best experts on this subject based on the ideXlab platform.

  • scanning geometry Influencing Factor on the quality of terrestrial laser scanning points
    Isprs Journal of Photogrammetry and Remote Sensing, 2011
    Co-Authors: Sylvie Soudarissanane, Roderik Lindenbergh, Massimo Menenti, Peter Teunissen
    Abstract:

    A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major Factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality.

  • Scanning geometry: Influencing Factor on the quality of terrestrial laser scanning points
    ISPRS Journal of Photogrammetry and Remote Sensing, 2011
    Co-Authors: Sylvie Soudarissanane, Roderik Lindenbergh, Massimo Menenti, Peter Teunissen
    Abstract:

    A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major Factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality. © 2011 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Roderik Lindenbergh - One of the best experts on this subject based on the ideXlab platform.

  • scanning geometry Influencing Factor on the quality of terrestrial laser scanning points
    Isprs Journal of Photogrammetry and Remote Sensing, 2011
    Co-Authors: Sylvie Soudarissanane, Roderik Lindenbergh, Massimo Menenti, Peter Teunissen
    Abstract:

    A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major Factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality.

  • Scanning geometry: Influencing Factor on the quality of terrestrial laser scanning points
    ISPRS Journal of Photogrammetry and Remote Sensing, 2011
    Co-Authors: Sylvie Soudarissanane, Roderik Lindenbergh, Massimo Menenti, Peter Teunissen
    Abstract:

    A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major Factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality. © 2011 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Massimo Menenti - One of the best experts on this subject based on the ideXlab platform.

  • scanning geometry Influencing Factor on the quality of terrestrial laser scanning points
    Isprs Journal of Photogrammetry and Remote Sensing, 2011
    Co-Authors: Sylvie Soudarissanane, Roderik Lindenbergh, Massimo Menenti, Peter Teunissen
    Abstract:

    A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major Factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality.

  • Scanning geometry: Influencing Factor on the quality of terrestrial laser scanning points
    ISPRS Journal of Photogrammetry and Remote Sensing, 2011
    Co-Authors: Sylvie Soudarissanane, Roderik Lindenbergh, Massimo Menenti, Peter Teunissen
    Abstract:

    A terrestrial laser scanner measures the distance to an object surface with a precision in the order of millimeters. The quality of the individual points in a point cloud, although directly affecting standard processing steps like point cloud registration and segmentation, is still not well understood. The quality of a scan point is influenced by four major Factors: instrument mechanism, atmospheric conditions, object surface properties and scan geometry. In this paper, the influence of the scan geometry on the individual point precision or local measurement noise is considered. The local scan geometry depends on the distance and the orientation of the scanned surface, relative to the position of the scanner. The local scan geometry is parameterized by two main parameters, the range, i.e. the distance from the object to the scanner and the incidence angle, i.e. the angle between incoming laser beam and the local surface normal. In this paper, it is shown that by studying the influence of the local scan geometry on the signal to noise ratio, the dependence of the measurement noise on range and incidence angle can be successfully modeled if planar surfaces are observed. The implications of this model is demonstrated further by comparing two point clouds of a small room, obtained from two different scanner positions: a center position and a corner position. The influence of incidence angle on the noise level is quantified on scans of this room, and by moving the scanner by 2 m, it is reduced by 20%. The improvement of the standard deviation is significant, going from 3.23 to 2.55 mm. It is possible to optimize measurement setups in such a way that the measurement noise due to bad scanning geometry is minimized and therefore contribute to a more efficient acquisition of point clouds of better quality. © 2011 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Xiaozhi Wu - One of the best experts on this subject based on the ideXlab platform.

  • theoretical models and Influencing Factor analysis for the temperature dependent tensile strength of ceramic fibers and their unidirectional composites
    Composite Structures, 2017
    Co-Authors: Jiaxing Shao, Weiguo Li, Yong Deng, Xianhe Zhang, Peiji Geng, Liming Chen, Xiaozhi Wu
    Abstract:

    Abstract In this paper, two physics-based temperature-dependent strength models for ceramic fibers were presented based on a critical failure energy density theory. These models included the combined effects of temperature, phase composition and oxidation on ceramic fiber strength. Good agreement between the model predictions and the experimental results was obtained. Based on the above models and the Cao and Thouless’s theory, a new temperature-dependent strength model for unidirectional ceramic fibers reinforced ceramic-matrix composites was developed. The good agreement between the predicted results and the experimental data fully validates the reasonability of this model. Compared with the Cao and Thouless’s model, the model is more practical and convenient to predict the temperature-dependent tensile strengths of the composites. The Influencing Factor analysis for ceramic fibers and their unidirectional composites were systematically conducted. Some new findings regarding their temperature-dependent tensile strengths were provided for the first time.