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TECHNICAL PAPERS

Smoothing of Noisy Laser Scanner Generated Meshes Using Polynomial Fitting and Neighborhood Erosion

[+] Author and Article Information
Miguel Vieira, Kenji Shimada, Tomotake Furuhata

The Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213

J. Mech. Des 126(3), 495-503 (Oct 01, 2003) (9 pages) doi:10.1115/1.1737381 History: Received May 01, 2003; Revised October 01, 2003
Copyright © 2004 by ASME
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Figures

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Front side panel of an automobile. The top row shows the original, noisy data and the bottom row shows the smoothed data. The left column shows a plot of the mean curvature and the right column shows the simulated reflection lines.
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Laplacian and curvature flow operators: the Laplacian operator (left) moves each vertex to the spatial average of its neighbors; the curvature flow operator (right) moves each vertex a distance equal to its estimated mean curvature in the direction opposite its normal.
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Polynomial smoothing operator: move each vertex in its median normal direction to a locally fitted polynomial h(u,v).
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The ideal mesh M0, left, whose vertices lie precisely on a regular parametric surface S0, and the noisy mesh M, right.
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The rows from top to bottom show, respectively, the original ideal mesh, the noisy mesh, and the smoothed mesh using the operator described in the paper. The roughness near the boundary is due to not moving boundary vertices. The mean curvature plot is shown on the left and the reflection line simulation is shown on the right.
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Driver-side front panel of an automobile. The left column shows plots of the mean curvature and the right column shows simulated reflection lines. From top to bottom are shown: the noisy mesh followed by the results of Laplacian, curvature flow, and polynomial smoothing. The best looking results are shown for each operator.
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The average and maximum displacement of the mesh vertices from their original positions. From left to right, the plots show Laplacian, curvature flow, and polynomial smoothing. These are for the smoothing operations shown in Fig. 8. The bottom graphs show the average and maximum displacement as a function of iterations for the different operators.
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Rear part of an automobile showing rear window, door handle, and gas tank. The left column shows plots of the mean curvature and the right column shows simulated reflection lines. From top to bottom are shown: the noisy mesh followed by the results of Laplacian, curvature flow, and polynomial smoothing. The best looking results are shown for each operator.
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The average and maximum displacement of the mesh vertices from their original positions. From left to right, the plots show Laplacian, curvature flow, and polynomial smoothing. These are for the smoothing operations shown in Fig. 10. The bottom graphs show the average and maximum displacement as a function of iterations for the different operators.
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Detail view of mesh shown in Fig. 10. The left column shows plots of the mean curvature and the right column shows simulated reflection lines. The original data is shown in the top row. From top to bottom are shown: the noisy mesh followed by the results of Laplacian, curvature flow, and polynomial smoothing. The best looking results are shown for each operator.
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The average and maximum displacement of the mesh vertices from their original positions. From left to right, the plots show Laplacian, curvature flow, and polynomial smoothing. These are for the smoothing operations shown in Fig. 10.

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