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Sensors 2018, 18(7), 2239; https://doi.org/10.3390/s18072239

Novel Adaptive Laser Scanning Method for Point Clouds of Free-Form Objects

1
School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
2
State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
Received: 10 May 2018 / Revised: 29 June 2018 / Accepted: 10 July 2018 / Published: 11 July 2018
(This article belongs to the Section Remote Sensors)

Abstract

Laser scanners are widely used to collect coordinates, also known as point-clouds, of three-dimensional free-form objects. For creating a solid model from a given point-cloud and transferring the data from the model, features-based optimization of the point-cloud to minimize the number if points in the cloud is required. To solve this problem, existing methods mainly extract significant points based on local surface variation of a predefined level. However, comprehensively describing an object’s geometric information using a predefined level is difficult since an object usually has multiple levels of details. Therefore, we propose a simplification method based on a multi-level strategy that adaptively determines the optimal level of points. For each level, significant points are extracted from the point cloud based on point importance measured by both local surface variation and the distribution of neighboring significant points. Furthermore, the degradation of perceptual quality for each level is evaluated by the adjusted mesh structural distortion measurement to select the optimal level. Experiments are performed to evaluate the effectiveness and applicability of the proposed method, demonstrating a reliable solution to optimize the adaptive laser scanning of point clouds for free-forms objects. View Full-Text
Keywords: adaptive representation; geometric multi-level; surface variation; radial basis function; perceptual quality adaptive representation; geometric multi-level; surface variation; radial basis function; perceptual quality
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Zang, Y.; Yang, B.; Liang, F.; Xiao, X. Novel Adaptive Laser Scanning Method for Point Clouds of Free-Form Objects. Sensors 2018, 18, 2239.

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