Abstract
The paper addresses the region search problem in three-dimensional (3D) space. The data used is a dynamically growing point cloud as it is typically gathered with a 3D-sensing device like a laser range-scanner. An encoding of space in combination with a new region search algorithm is introduced. The algorithm allows for fast access to spherical subsets of variable size. An octree based and a balanced binary tree based implementation are discussed. Finally, experiments concerning processing time are shown.
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© 2005 Springer-Verlag Berlin Heidelberg
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Wahl, E., Hirzinger, G. (2005). A Method for Fast Search of Variable Regions on Dynamic 3D Point Clouds. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds) Pattern Recognition. DAGM 2005. Lecture Notes in Computer Science, vol 3663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550518_26
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DOI: https://doi.org/10.1007/11550518_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28703-2
Online ISBN: 978-3-540-31942-9
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