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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:2012 2nd International Conference on Computer Science and Network Technology s. 1350 - 1353
Hlavní autoři: Yu, Haifeng, Wang, Rui, Chen, Junli, Liu, Liang, Wan, Wanggen
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.12.2012
Témata:
Data models
Estimation
normal vector
Octree
Octrees
Point cloud compression
saliency
simplification
Solid modeling
Three-dimensional displays
Vectors
Visual systems
Visualization
ISBN:1467329630, 9781467329637
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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