Abstract

Point cloud models are a common shape representation for several reasons. Three-dimensional scanning devices are widely used nowadays and points are an attractive primitive for rendering complex geometry. Nevertheless, there is not much literature on collision detection for point cloud models. This paper presents a novel collision detection algorithm for large point cloud models using voxels, octrees and bounding spheres hierarchies (BSH). The scene graph is divided in voxels. The objects of each voxel are organized intoan octree. Due to the high number of points in the scene, each non-empty cell of the octree is organized in a bounding sphere hierarchy, based on an R-tree hierarchy like structure. The BSH hierarchies are used to group neighboring points and filter out very quickly parts of objects that do not interact with other models. Points derived from laser scanned data typically are not segmented and can have arbitrary spatial resolution thus introducing computational and modeling issues. We address these issues and our results show that the proposed collision detection algorithm effectively finds intersections between point cloud models since it is able to reduce the number of bounding volume checks and updates

Highlights

  • Point cloud models are an increasingly attractive representation used as the basis to capture and measure reality rapidly in an increasing number of applications such as environmental surveying, structure analysis and archaeology [1]

  • This paper describes a novel collision detection algorithm for point cloud models

  • The points of each non-empty cell of the octree are organized in a bounding sphere hierarchy (BSH), like an R-tree data structure, defined in its own local coordinate system

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Summary

INTRODUCTION

Point cloud models are an increasingly attractive representation used as the basis to capture and measure reality rapidly in an increasing number of applications such as environmental surveying, structure analysis and archaeology [1]. Interactive virtual environments often need very fast collision detection queries to simulate physical behavior and to allow the user to interact. There is practically no literature on determining collisions between two sets of points. This paper describes a novel collision detection algorithm for point cloud models. The scene graph is organized into voxels. To speed up the process of finding collisions, each voxel, is partitioned by an octree. The points of each non-empty cell of the octree are organized in a bounding sphere hierarchy (BSH), like an R-tree data structure, defined in its own local coordinate system.

RELATED WORK
POINT CLOUD HIERARCHY
BOUNDING SPHERE HIERARCHY FOR THE COLLISION DETECTION PROBLEM
COLLISION DETECTION ALGORITHM
EXPERIMENTAL RESULTS
VIII. CONCLUSIONS AND FUTURE WORK

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