Saliency computation and simplification of point cloud data

According to human visual sensitivity, in this paper, we present a new simplification of point cloud based on point saliency. In order to find the nearest K points, we need to divide the space of Point cloud firstly. Secondly, we compute the normal vector and saliency of every point. At last, we com...

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Bibliographic Details
Published in:2012 2nd International Conference on Computer Science and Network Technology pp. 1350 - 1353
Main Authors: Yu, Haifeng, Wang, Rui, Chen, Junli, Liu, Liang, Wan, Wanggen
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2012
Subjects:
Data models
Estimation
normal vector
Octree
Octrees
Point cloud compression
saliency
simplification
Solid modeling
Three-dimensional displays
Vectors
Visual systems
Visualization
ISBN:1467329630, 9781467329637
Online Access:Get full text
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Summary:According to human visual sensitivity, in this paper, we present a new simplification of point cloud based on point saliency. In order to find the nearest K points, we need to divide the space of Point cloud firstly. Secondly, we compute the normal vector and saliency of every point. At last, we combine octree structure and saliency to simplify point cloud data. Experiments show that our method can well preserve the point cloud in visual sensitivity area.
ISBN:1467329630
9781467329637
DOI:10.1109/ICCSNT.2012.6526171