Generation of volume/surface octree from range data
Chien, C.H.
Sim, Y.B.
Aggarwal, J.K.
Dept. of Comput. Sci., Carnegie-Mellon Univ., Pittsburgh, PA;
This paper appears in: Computer Vision and Pattern Recognition, 1988. Proceedings CVPR '88., Computer Society Conference on
Publication Date: 5-9 Jun 1988
On page(s): 254-260
Meeting Date: 06/05/1988 - 06/09/1988
Location: Ann Arbor, MI, USA
ISBN: 0-8186-0862-5
References Cited: 14
INSPEC Accession Number: 3258523
Digital Object Identifier: 10.1109/CVPR.1988.196245
Current Version Published: 2002-08-06
Abstract
The authors propose a scheme to generate the volume/surface octree
structure from range data. The scheme is similar to that of the quadtree
generation algorithm. However, in this case, each node in the quadtree
is a binary tree corresponding to a range data point. Consequently, the
octree of the viewed object can be generated efficiently by merging the
neighboring binary trees recursively. Surface normals can be computed
directly from the range image. They are encoded into associated binary
trees and subsequently propagated to the corresponding octree nodes
during the merging process. Since 3-D information of the viewed object
is available in each range image, the proposed scheme is capable of
capturing the concave structures in objects, which cannot be detected
from intensity model construction. Furthermore, since the algorithms
developed in this research are essentially recursive tree traversal
procedures, they are suitable for parallel implementation
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