THE SPARSE REPRESENTATION OF POINT CLOUD AND ITS APPLICATIONS

ZHANG Yong; NI Ping; WU Xin

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THE SPARSE REPRESENTATION OF POINT CLOUD AND ITS APPLICATIONS

ZHANG Yong 1 *,NI Ping 2 #,WU Xin 1

1.Beijing University of Technology,College of Metropolitan Transportation,Beijing,100124

2.Beijing Transportation Information Center

*Correspondence author

#Submitted by

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Funding: Specialized Research Fund for the Doctoral Program of Higher Education（No.No. 20121103120034）, Beijing Natural Science Foundation （No.No. 4142010）, National Science Foundation of China （No.No.61300065）, Beijing Municipal Science and Technology Project （No.No. Z151100002115040）

Opened online:20 June 2016

Accepted by: none

Citation: ZHANG Yong,NI Ping,WU Xin.THE SPARSE REPRESENTATION OF POINT CLOUD AND ITS APPLICATIONS[OL]. [20 June 2016] http://en.paper.edu.cn/en_releasepaper/content/4696958

Point cloud is one of the most important tools for representing geometry in computer vision and computer graphics. In order to represent geometry with high accuracy, point cloud usually has large size and complicated structures, which result in great difficulties in storage, processing and transmission on limited bandwidth. This paper proposes a way to sparsely represent point cloud, consisting of a cluster-based point cloud normalization procedure, dictionary learning under the context of sparse point clouds, and compressing and reconstructing point clouds based on the compressive sensing theory. The method paves the way to effectively represent point clouds. The experimental results not only show feasibility of sparse representation of point clouds but also demonstrate competitive performance in terms of accurate reconstruction.

Keywords:Computer Application;Compressive Sensing;Point Cloud;Cluster Analysis; Over-complete Dictionary

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