Automatic Indoor 3D Surface Reconstruction with Segmented Building and Object Elements

被引:7
|
作者
Turner, Eric [1 ]
Zakhor, Avideh [1 ]
机构
[1] Univ Calif Berkeley, Berkeley, CA 94720 USA
来源
2015 INTERNATIONAL CONFERENCE ON 3D VISION | 2015年
关键词
D O I
10.1109/3DV.2015.48
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Automatic generation of 3D indoor building models is important for applications in augmented and virtual reality, indoor navigation, and building simulation software. This paper presents a method to generate high-detail watertight models from laser range data taken by an ambulatory scanning device. Our approach can be used to segment the permanent structure of the building from the objects within the building. We use distinct techniques to mesh the building structure and the objects to efficiently represent large planar surfaces, such as walls and floors, while still preserving the fine detail of segmented objects, such as furniture or light fixtures. Our approach is scalable enough to be applied on large models composed of several dozen rooms, spanning over 14,000 square feet. We experimentally verify this method on several datasets from diverse building environments.
引用
收藏
页码:362 / 370
页数:9
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