16 March 2015 On detailed 3D reconstruction of large indoor environments
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Abstract
In this paper we present techniques for highly detailed 3D reconstruction of extra large indoor environments. We discuss the benefits and drawbacks of low-range, far-range and hybrid sensing and reconstruction approaches. The proposed techniques for low-range and hybrid reconstruction, enabling the reconstruction density of 125 points/cm3 on large 100.000 m3 models, are presented in detail. The techniques tackle the core challenges for the above requirements, such as a multi-modal data fusion (fusion of a LIDAR data with a Kinect data), accurate sensor pose estimation, high-density scanning and depth data noise filtering. Other important aspects for extra large 3D indoor reconstruction are the point cloud decimation and real-time rendering. In this paper, we present a method for planar-based point cloud decimation, allowing for reduction of a point cloud size by 80-95%. Besides this, we introduce a method for online rendering of extra large point clouds enabling real-time visualization of huge cloud spaces in conventional web browsers.
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Egor Bondarev, Egor Bondarev, "On detailed 3D reconstruction of large indoor environments", Proc. SPIE 9399, Image Processing: Algorithms and Systems XIII, 93990G (16 March 2015); doi: 10.1117/12.2085111; https://doi.org/10.1117/12.2085111
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