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Greedy Cuts: An advancing front terrain triangulation algorithm 98

Greedy Cuts: An advancing front terrain triangulation algori...

引用

6th ACM International Symposium on Advances in Geographic Information Systems, GIS 1998

作者： Silva, Cláudio T. Mitchell, Joseph S.B. Visual and Geometric Computing Group IBM T.J. Watson Research Center P.O. Box 704 Yorktown HeightsNY10598 United States Department of Applied Mathematics and Statistics State University of New York at Stony Brook Stony BrookNY11794-3600 United States

ISBN: (纸本)1581131151

We apply an advancing front technique to the problem of simplification of dense digitized terrain models. While most simplification algorithms have been based on either incremental refinement or decimation techniques, our Greedy-Cuts algorithm uses a simple triangulation-growth procedure. We improve on our earlier advancing-front technique, which was not able to backtrack in its triangulation decisions, resulting in triangulations that may have low quality. The new algorithm we propose overcomes this shortcoming by maintaining two "fronts", a real front and a virtual front, that bound between them a region of the terrain that has only a tentative triangulation. By allowing simple local operations (edge collapses and edge flips) in the tentative triangulation, we are able to avoid many of the artifacts of the earlier advancing-front technique, while not significantly affecting memory usage. GcTin, our terrain triangulation tool, is publicly available for research purposes. The original version of GcTin has been in use at several commercial and non-commercial sites since 1995. The new algorithms described here are integrated in the latest release and result in substantially improved triangulations. © 1998 ACM.

关键词： Triangulation

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An exact interactive time visibility ordering algorithm for polyhedral cell complexes

An exact interactive time visibility ordering algorithm for ...

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1998 IEEE Symposium on Volume visualization, VVS 1998

作者： Silva, Cláudio T. Mitchell, Joseph S.B. Williams, Peter L. Visual and Geometric Computing Group IBM T. J. Watson Research Center P.O. Box 704 Yorktown HeightsNY10598 United States Department of Applied Mathematics and Statistics State University of New York at Stony Brook Stony BrookNY11794-3600 United States Computing Group IBM T. J. Watson Research Center P.O. Box 704 Yorktown HeightsNY10598 United States

ISBN: (纸本)1581131054

A visibility ordering of a set of objects, from a given viewpoint, is a total order on the objects such that if object a obstructs object b, then b precedes a in the ordering. Such order-ings are extremely useful for rendering volumetric data. We present an algorithm that generates a visibility ordering of the cells of an unstructured mesh, provided that the cells are convex polyhedra and nomntersecting, and that the visibility ordering graph does not contain cycles. The overall mesh may be nonconvex and it may have disconnected components. Our technique employs the sweep paradigm to determine an ordering between pairs of exterior (mesh boundary) cells which can obstruct one another. It then builds on Williams' MPVO algorithm [33] which exploits the ordering implied by adjacencies within the mesh. The partial ordering of the exterior cells found by sweeping is used to augment the DAG created in Phase II of the MPVO algorithm. Our method thus removes the assumption of the MPVO algorithm that the mesh be convex and connected, and thereby allows us to extend MPVO algorithm, without using the heuristics that were originally suggested by Williams (and are sometimes problematic). The resulting XMPVO algorithm has been analyzed, and a variation of it has been implemented for unstructured tetrahedral meshes;we provide experimental evidence that it performs very well in practice. Copyright 1998 IEEE.

关键词： Finite element method

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Deep lidar odometry 4

Deep lidar odometry

引用

4th ISPRS Geospatial Week 2019

作者： Li, Q. Wang, C. Chen, S. Li, X. Wen, C. Cheng, M. Li, J. Fujian Key Lab. of Sensing and Comp. for Smart City and the Sch. of Info. Science and Engineering Xiamen University Xiamen361005 China Fujian Collaborative Innovation Center for Big Data Applications in Governments Fuzhou350003 China Geometric and Visual Computing Group Louisiana State University LA70808 United States GeoSTARS Lab Department of Geography and Environmental Management University of Waterloo Canada

Most existing lidar odometry estimation strategies are formulated under a standard framework that includes feature selection, and pose estimation through feature matching. In this work, we present a novel pipeline called LO-Net for lidar odometry estimation from 3D lidar scanning data using deep convolutional networks. The network is trained in an end-to-end manner, it infers 6-DoF poses from the encoded sequential lidar data. Based on the new designed mask-weighted geometric constraint loss, the network automatically learns effective feature representation for the lidar odometry estimation problem, and implicitly exploits the sequential dependencies and dynamics. Experiments on benchmark datasets demonstrate that LO-Net has similar accuracy with the geometry-based approach. © Authors 2019.

关键词： Motion estimation

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An exact interactive time visibility ordering algorithm for polyhedral cell complexes

An exact interactive time visibility ordering algorithm for ...

引用

IEEE Symposium on Volume visualization and Graphics

作者： C.T. Silva J.S.B. Mitchell P.L. Williams IBM T J Watson Research Center Visual and Geometric Computing Group Yorktown Heights NY USA Department of Applied Mathematics and Statistics State University of New York Stony Brook Stony Brook NY USA IBM T J Watson Research Center Data Explorer (DX) Research Group Yorktown Heights NY USA

A visibility ordering of a set of objects, from a given viewpoint, is a total order on the objects such that if object a obstructs object b, then b precedes a in the ordering. Such orderings are extremely useful for rendering volumetric data. The authors present an algorithm that generates a visibility ordering of the cells of an unstructured mesh, provided that the cells are convex polyhedra and nonintersecting, and that the visibility ordering graph does not contain cycles. The overall mesh may be nonconvex and it may have disconnected components. The technique employs the sweep paradigm to determine an ordering between pairs of exterior (mesh boundary) cells which can obstruct one another. It then builds on Williams' (1992) MPVO algorithm which exploits the ordering implied by adjacencies within the mesh. The partial ordering of the exterior cells found by sweeping is used to augment the DAG created in Phase II of the MPVO algorithm. The method thus removes the assumption of the MPVO algorithm that the mesh be convex and connected, and thereby allows one to extend the MPVO algorithm, without using the heuristics that were originally suggested by Williams (and are sometimes problematic). The resulting XMPVO algorithm has been analyzed, and a variation of it has been implemented for unstructured tetrahedral meshes; they provide experimental evidence that it performs very well in practice.

关键词： Mesh generation Performance analysis Algorithm design and analysis

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