Semantic Segmentation of 3D Point Cloud to Virtually Manipulate Real Living Space

被引：9

作者：

Ishikawa, Yuki ^{[1
]}

Hachiuma, Ryo ^{[1
]}

Ienaga, Naoto ^{[1
]}

Kuno, Wakaba ^{[1
]}

Sugiura, Yuta ^{[1
]}

Saito, Hideo ^{[1
]}

机构：

[1] Keio Univ, Yokohama, Kanagawa, Japan

来源：

2019 12TH ASIA PACIFIC WORKSHOP ON MIXED AND AUGMENTED REALITY (APMAR) | 2019年

关键词：

furniture arrangement; semantic segmentation; virtual reality;

D O I：

10.1109/apmar.2019.8709156

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper presents a method for the virtual manipulation of real living space using semantic segmentation of a 3D point cloud captured in the real world. We applied PointNet to segment each piece of furniture from the point cloud of a real indoor environment captured by moving a RGBD camera. For semantic segmentation, we focused on local geometric information not used in PointNet, and we proposed a method to refine the class probability of labels attached to each point in PointNet's output. The effectiveness of our method was experimentally confirmed. We then created 3D models of real-world furniture using a point cloud with corrected labels, and we virtually manipulated real living space using Dollhouse VR, a layout system.

引用

页码：63 / 69

页数：7

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