基于kinect的3D扫描数据集

Alexandros Doumanoglou, S. Asteriadis, D. Alexiadis, D. Zarpalas, P. Daras
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引用次数: 10

摘要

在此基础上,提出了一种新的面向公众的面向三维重建的数据集。它包括使用转盘对小型物体进行多视图范围扫描。使用微软Kinect传感器和精确的激光扫描仪(Vivid VI-700非接触式3D数字化仪)捕获距离扫描,其重建可以作为地面真实数据。尽管Kinect已经吸引了许多研究人员和家庭爱好者的注意,但由于缺乏相关的Kinect数据集,该数据集的构建受到了激励。因此,构建该数据集背后的核心思想是允许使用Kinect传感器提取的点集的3D表面重建方法的验证。该数据集包括对59个物体的多视角范围扫描,以及可用于Kinect深度数据3D重建领域实验的必要校准信息。选择了两种知名的三维重建方法,并对数据集进行了应用,以证明其在三维重建领域的适用性,以及所面临的挑战。此外,提出了合适的三维重建评价方法。最后,由于数据集来自相似对象的类别,它也可以用于分类目的,使用提供的2.5D/3D特征。
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A dataset of Kinect-based 3D scans
Hereby, a new publicly available 3D reconstruction-oriented dataset is presented. It consists of multi-view range scans of small-sized objects using a turntable. Range scans were captured using a Microsoft Kinect sensor, as well as an accurate laser scanner (Vivid VI-700 Non-contact 3D Digitizer), whose reconstructions can serve as ground-truth data. The construction of this dataset was motivated by the lack of a relevant Kinect dataset, despite the fact that Kinect has attracted the attention of many researchers and home enthusiasts. Thus, the core idea behind the construction of this dataset, is to allow the validation of 3D surface reconstruction methodologies for point sets extracted using Kinect sensors. The dataset consists of multi-view range scans of 59 objects, along with the necessary calibration information that can be used for experimentation in the field of 3D reconstruction from Kinect depth data. Two well-known 3D reconstruction methods were selected and applied on the dataset, in order to demonstrate its applicability in the 3D reconstruction field, as well as the challenges that arise. Additionally, the appropriate 3D reconstruction evaluation methodology is presented. Finally, as the dataset comes in classes of similar objects, it can also be used for classification purposes, using the provided 2.5D/3D features.
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