Published 2002
| Version v1
Report
The expected number of 3D visibility events is linear
Contributors
Others:
- Geometry, Algorithms and Robotics (PRISME) ; Centre Inria d'Université Côte d'Azur (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- School of Computer Science [Ottawa] ; University of Ottawa [Ottawa]
- Models, algorithms and geometry for computer graphics and vision (ISA) ; INRIA Lorraine ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)-Université Henri Poincaré - Nancy 1 (UHP)-Université Nancy 2-Institut National Polytechnique de Lorraine (INPL)-Centre National de la Recherche Scientifique (CNRS)
- School of Computing - Soongsil University, Séoul ; Soongsil University, Seoul
- INRIA
Description
In this paper, we show that, amongst n uniformly distributed unit balls in R^3, the expected number of maximal non-occluded line segments tangent to four balls is linear, considerably improving the previously known upper bound. Using our techniques we show a linear bound on the expected size of the visibility complex, a data structure encoding the visibility information of a scene, providing evidence that the storage requirement for this data structure is not necessarily prohibitive. Our results generalize in various directions. We show that the linear bound on the expected number of maximal non-occluded line segments that are not too close to the boundary of the scene and tangent to four unit balls extends to balls of various but bounded radii, to polyhedra of bounded aspect ratio, and even to non-fat 3D objects such as polygons of bounded aspect ratio. We also prove that our results extend to other distributions such as the Poisson distribution. Finally, we indicate how our probabilistic analysis provides new insight on the expected size of other global visibility data structures, notably the aspect graph.
Additional details
Identifiers
- URL
- https://inria.hal.science/inria-00071914
- URN
- urn:oai:HAL:inria-00071914v1
Origin repository
- Origin repository
- UNICA