RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments
RGB-D mapping: Using Kinect-style depth cameras for dense 3D modeling of indoor environments
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DOI：
10.1177/0278364911434148
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发表时间：
2012-04-01
影响因子：
9.2
通讯作者：
Fox, Dieter
中科院分区：
文献类型：
--
作者：
Henry, Peter;Krainin, Michael;Fox, Dieter
RGB-D相机（如Microsoft Kinect）是一种新颖的传感系统，可捕获RGB图像沿着每像素深度信息。在本文中，我们将研究如何使用这种相机来构建密集的室内环境的3D地图。这样的地图在机器人导航，操纵，语义映射和远程呈现中有应用。我们提出了RGB-D映射，一个完整的3D映射系统，利用一种新的联合优化算法相结合的视觉特征和基于形状的对齐。视觉和深度信息也被结合用于基于视图的环闭合检测，然后进行姿势优化以实现全局一致的地图。我们在两个大型室内环境中评估了RGB-D映射，并表明它有效地结合了RGB-D相机提供的视觉和形状信息。
RGB-D cameras (such as the Microsoft Kinect) are novel sensing systems that capture RGB images along with per-pixel depth information. In this paper we investigate how such cameras can be used for building dense 3D maps of indoor environments. Such maps have applications in robot navigation, manipulation, semantic mapping, and telepresence. We present RGB-D Mapping, a full 3D mapping system that utilizes a novel joint optimization algorithm combining visual features and shape-based alignment. Visual and depth information are also combined for view-based loop-closure detection, followed by pose optimization to achieve globally consistent maps. We evaluate RGB-D Mapping on two large indoor environments, and show that it effectively combines the visual and shape information available from RGB-D cameras.