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Active vision for 3D indoor scene reconstruction using a 3D camera on a pan-tilt mechanism
Advanced Robotics ( IF 2 ) Pub Date : 2021-01-21 , DOI: 10.1080/01691864.2021.1875042
Mateja Hržica 1 , Robert Cupec 1 , Ivan Petrović 2
Affiliation  

We present a novel approach to automatic indoor scene reconstruction from RGB-D images acquired from a single viewpoint using active vision. The proposed method is designed to select the next view with sufficient information for reliable registration. The next view is selected based on the percentage of unexplored scene regions captured inside the field of view and the information content in the overlapping region between the image acquired from the next view and one of the previously acquired images. It is required that this overlapping region contains surfaces with different orientations, whose alignment provides a reliable estimation of the relative camera orientation. The point correspondences between views are established using the assumption of fixed viewpoint, imprecise information about relative view orientation and local surface normal, without need for features based on texture or distinctive local shape. After completing a scan, the 3D scene model is constructed by performing registration of the acquired depth images. Two algorithms are considered for that purpose: a point-to-plane ICP with point weighting based on the properties of the measurement noise and TEASER++. The proposed method is tested on the synthetic dataset Replica.



中文翻译:

使用3D摄像机在横摇倾斜装置上进行3D室内场景重建的主动视觉

我们提出了一种新颖的方法,可以从使用主动视觉从单个视点获取的RGB-D图像进行自动室内场景重建。提出的方法旨在选择具有足够信息的下一个视图,以进行可靠注册。基于从视野内捕获的未探索场景区域的百分比以及从下一视图获取的图像与先前获取的图像之一之间的重叠区域中的信息内容,选择下一视图。要求此重叠区域包含具有不同方向的表面,其对齐方式可提供相对摄像机方向的可靠估计。使用固定视点,关于相对视点方向和局部表面法线的不精确信息的假设来建立视图之间的点对应关系,无需基于纹理或独特的局部形状的特征。完成扫描后,通过对获取的深度图像进行配准来构建3D场景模型。为此,考虑了两种算法:基于测量噪声和TEASER ++的特性的点到点ICP的点加权。在合成数据集副本上测试了该方法。

更新日期:2021-02-09
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