Matching Technology of Point Cloud Models Based on Combination Features

Xu Zhang; Xue Сhang Zhang; Jiqiang Li; Jiang Xiong Li

doi:10.4028/www.scientific.net/AMR.97-101.3493

Paper Titles

Research on Virtual Design and Simulation System for Manipulators of Multi-Degree of Freedom
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Particle Swarm Optimization with Adaptive Inertia Weight and its Application in Optimization Design
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Dynamic Analysis of a Rotatable Mobile Robot Based on Turning Pose
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Matching Technology of Point Cloud Models Based on Combination Features
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Research on Parameters Optimization of Virtual NC Milling Based on Parallelism Selection Genetic Algorithm
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Dynamic Load Sharing Characteristic of Planetary Gear System with Load Balancing Mechanism
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Optimum Design of Roll Ring
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Optimal Layout of the Irregular Parts with Neural Networks Hybrid Algorithm
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 97-101Matching Technology of Point Cloud Models Based on...

Matching Technology of Point Cloud Models Based on Combination Features

Abstract:

A combination features based technology is proposed to matching point cloud models. Firstly, automatically segment the point cloud to get ruled shape data from which the statistics features are extracted. Calculate the distance and angle between component elements of statistics feature and datum plane. The distance and angle constraints are introduced to automatically search correspondence statistics features of overlap region and the optimal combination of statistics features. The optimal combination is coupled for combination feature. If combination feature can completely identify pose of model, we call this as completely matching question; otherwise, this is called as partly matching question. For the latter, adjust the degrees of freedom which are not constrained and then precisely match the models using ICP algorithm. The examples show the proposed algorithm is simple and efficient, and the matching results are stable, reliable and convergent to a global optimal solution.

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Periodical:

Advanced Materials Research (Volumes 97-101)

Pages:

3493-3497

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.97-101.3493

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Online since:

March 2010

Authors:

Xu Zhang, Xue Сhang Zhang, Jiqiang Li, Jiang Xiong Li

Keywords:

Combination Feature, Correspondence Feature, Matching

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