Preprint Article Version 1 This version is not peer-reviewed

Calculating Point Cloud Object Volume Using Co-Opposite-Direction Slicing Method

Version 1 : Received: 21 November 2019 / Approved: 22 November 2019 / Online: 22 November 2019 (05:37:00 CET)

How to cite: Li, B.; Bi, X.; Peng, C.; Chen, Y.; Zhao, X.; Yang, C. Calculating Point Cloud Object Volume Using Co-Opposite-Direction Slicing Method. Preprints 2019, 2019110253 (doi: 10.20944/preprints201911.0253.v1). Li, B.; Bi, X.; Peng, C.; Chen, Y.; Zhao, X.; Yang, C. Calculating Point Cloud Object Volume Using Co-Opposite-Direction Slicing Method. Preprints 2019, 2019110253 (doi: 10.20944/preprints201911.0253.v1).

Abstract

Although the Slicing Method (SM) is effective for calculating the volume of point cloud objects (PCOs), it is restricted in terms of applicability and practicability because of a certain contingency and directional defects. The Co-Opposite-Direction Slicing Method (CODSM) proposed in this paper is an improved method for calculating PCO volume by increasing parallel (co-opposite-direction) observation and considering the two-way mean as the result. This method takes full advantage of the mutual offsetting of random errors and the compensation of systematic directional errors, which can effectively overcome (or mitigate) the effect of random errors and reduce the effect of systematic errors in SM. In this paper, two typical objects, a cone model and a stone lion base, are the examples for calculating PCO volume using CODSM. The results show that CODSM has all the inherent advantages of SM and effectively weakens the volatility of random errors and the directionality of systematic errors from SM. Therefore, CODSM is a robust configuration upgrade of SM.

Subject Areas

point cloud objects (PCOs); volume calculation (VC); co-opposite-direction slicing method (CODSM); systematic directional errors; random errors

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