Fast 3D edge detection by using decision tree from depth image

Author(s):  
Masaya Kaneko ◽  
Takahiro Hasegawa ◽  
Yuji Yamauchi ◽  
Takayoshi Yamashita ◽  
Hironobu Fujiyoshi ◽  
...  
2015 ◽  
Author(s):  
Miguel Angel Villanueva Portela-CA ◽  
Ricardo Emiro Ramirez Heredia

2013 ◽  
Vol 63 ◽  
pp. 710-719 ◽  
Author(s):  
S. Ontiveros ◽  
J.A. Yagüe ◽  
R. Jiménez ◽  
F. Brosed

1991 ◽  
Vol 9 (4) ◽  
pp. 203-214 ◽  
Author(s):  
Oliver Monga ◽  
Rachid Deriche ◽  
Grégoire Malandain ◽  
Jean Pierre Cocquerez

Author(s):  
H. Ni ◽  
X. G. Lin ◽  
J. X. Zhang

Edge detection has been one of the major issues in the field of remote sensing and photogrammetry. With the fast development of sensor technology of laser scanning system, dense point clouds have become increasingly common. Precious 3D-edges are able to be detected from these point clouds and a great deal of edge or feature line extraction methods have been proposed. Among these methods, an easy-to-use 3D-edge detection method, AGPN (Analyzing Geometric Properties of Neighborhoods), has been proposed. The AGPN method detects edges based on the analysis of geometric properties of a query point’s neighbourhood. The AGPN method detects two kinds of 3D-edges, including boundary elements and fold edges, and it has many applications. This paper presents three applications of AGPN, i.e., 3D line segment extraction, ground points filtering, and ground breakline extraction. Experiments show that the utilization of AGPN method gives a straightforward solution to these applications.


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