Sphere Packings for Arbitrary Objects

Weller, René

doi:10.1007/978-3-319-01020-5_4

Cited by 1 publication

(2 citation statements)

References 36 publications

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“…Packing issues may be divided into two categories based on the utilized packing structures: ordered packing and disorderly packing [31]. When considering the differences between space containers, the problem becomes the packing of either regular objects or irregular objects [32,33].…”

Section: Sphere Packingmentioning

confidence: 99%

“…The research was restricted to integer radii, and the studied problem was proven to be an NP-completeness problem. Weller [33] proposed a sphere packing method for arbitrary object mesh models. The arbitrary object was voxelized first, and the value of each voxel was set to be the distance to the closest triangle on the surface of the object.…”

Section: Sphere Packingmentioning

confidence: 99%

See 1 more Smart Citation

Volumetric Representation and Sphere Packing of Indoor Space for Three-Dimensional Room Segmentation

Yang

Che

Zuo

et al. 2021

IJGI

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Room segmentation is a basic task for the semantic enrichment of point clouds. Recent studies have mainly projected single-floor point clouds to binary images to realize two-dimensional room segmentation. However, these methods have difficulty solving semantic segmentation problems in complex 3D indoor environments, including cross-floor spaces and rooms inside rooms; this is the bottleneck of indoor 3D modeling for non-Manhattan worlds. To make full use of the abundant geometric and spatial structure information in 3D space, a novel 3D room segmentation method that realizes room segmentation directly in 3D space is proposed in this study. The method utilizes volumetric representation based on a VDB data structure and packs an indoor space with a set of compact spheres to form rooms as separated connected components. Experimental results on different types of indoor point cloud datasets demonstrate the efficiency of the proposed method.

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Section: Sphere Packingmentioning

confidence: 99%

Section: Sphere Packingmentioning

confidence: 99%