Bayesian graph-cut optimization for wall surfaces reconstruction in indoor environments

被引：30

作者：

Michailidis, Georgios-Tsampikos ^{[1
]}

Pajarola, Renato ^{[1
]}

机构：

[1] Univ Zurich, Dept Informat, Binzmhlestr 14, CH-8050 Zurich, Switzerland

来源：

VISUAL COMPUTER | 2017年 / 33卷 / 10期

关键词：

Scene reconstruction; Point cloud processing; LiDAR reconstruction; Wall surface reconstruction; Wall openings detection;

D O I：

10.1007/s00371-016-1230-3

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

In this paper, a new method capable to extract the wall openings (windows and doors) of interior scenes from point clouds under cluttered and occluded environments is presented. For each wall surface extracted by the polyhedral model of a room, our method constructs a cell complex representation, which is used for the wall object segmentation using a graph-cut method. We evaluate the results of the proposed approach on real-world 3D scans of indoor environments and demonstrate its validity.

引用

页码：1347 / 1355

页数：9

共 32 条

[1] Bayesian graph-cut optimization for wall surfaces reconstruction in indoor environments
Georgios-Tsampikos Michailidis
Renato Pajarola
The Visual Computer, 2017, 33 : 1347 - 1355
[2] Indoor scene reconstruction using feature sensitive primitive extraction and graph-cut
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