<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Point cloud is an important data format that can completely express scene information. In recent years, with the dramatic increase of polygon complexity of model, the advantage of point model becomes more and more obvious. The point-based computer graphics, which takes point cloud as the research object, has aroused the attention of more and more people, and has been widely used in many fields such as computer vision, automatic driving and robot. In this paper, the point cloud segmentation methods and research status were reviewed in detail, the representative algorithms of each type of methods were analyzed and introduced, and the basic ideas, advantages and disadvantages of each type of methods were summarized. Finally, the problems faced by the segmentation technology and the development direction of the future work are prospected.</p>
</abstract>

Point cloud is an important data format that can completely express scene information. In recent years, with the dramatic increase of polygon complexity of model, the advantage of point model becomes more and more obvious. The point-based computer graphics, which takes point cloud as the research object, has aroused the attention of more and more people, and has been widely used in many fields such as computer vision, automatic driving and robot. In this paper, the point cloud segmentation methods and research status were reviewed in detail, the representative algorithms of each type of methods were analyzed and introduced, and the basic ideas, advantages and disadvantages of each type of methods were summarized. Finally, the problems faced by the segmentation technology and the development direction of the future work are prospected.

A Review of Segmentation Technology Based on 3D Point Cloud

International Journal of Advanced Network, Monitoring and Controls

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"A Review of Segmentation Technology Based on 3D Point Cloud"}

Point cloud is an important data format that can completely express scene information. In recent years, with the dramatic increase of polygon complexity of...

Segmentation type	Tightness	To deal with noise	The processing time	Application Scenarios
Edge	worst	difficult	fast	Large scene segmentation with a priori capability
Region	best	perfect	Depends on the number of point	High precision segmentation scene
Cluster	better	suitable for detecting some objects with special shape from the chaotic point cloud	fast	Clustering is the division of a data set into different classes according to a particular criterion
Graph	worst	general	It depends on the number of edges	More for image segmentation

A Review of Segmentation Technology Based on 3D Point Cloud

Online veröffentlicht: 19. Apr. 2021

Seitenbereich: 35 - 40

DOI: https://doi.org/10.21307/ijanmc-2021-006

Schlüsselwörter
Virtual, Point Cloud, 3D Model, Segment

© 2021 Liu Baolong, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

COMPARISON OF VARIOUS SEGMENTATION ALGORITHMS

A Review of Segmentation Technology Based on 3D Point Cloud

Online veröffentlicht: 19. Apr. 2021

Seitenbereich: 35 - 40

DOI: https://doi.org/10.21307/ijanmc-2021-006

SchlüsselwörterVirtual, Point Cloud, 3D Model, Segment

© 2021 Liu Baolong, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

COMPARISON OF VARIOUS SEGMENTATION ALGORITHMS

Schlüsselwörter
Virtual, Point Cloud, 3D Model, Segment