论文标题
基于图的语义单眼定位和映射的对象结构点表示
Object Structural Points Representation for Graph-based Semantic Monocular Localization and Mapping
论文作者
论文摘要
单眼语义同时定位和映射（SLAM）的有效对象级别表示仍然缺乏广泛接受的解决方案。在本文中，我们提出了基于结构点的有效表示的使用，以基于姿势绘制的配方在单眼语义大满贯系统中用作地标的几何形状。特别地，提出了姿势图中的地标节点的反向深度参数化，以存储对象位置，方向和大小/比例。所提出的配方是一般的，可以应用于不同的几何形状。在本文中，我们关注的是室内环境，其中人为工件通常具有平面矩形形状，例如窗户，门，橱柜等。模拟中的实验表现出良好的性能，尤其是在对象几何重建中。
Efficient object level representation for monocular semantic simultaneous localization and mapping (SLAM) still lacks a widely accepted solution. In this paper, we propose the use of an efficient representation, based on structural points, for the geometry of objects to be used as landmarks in a monocular semantic SLAM system based on the pose-graph formulation. In particular, an inverse depth parametrization is proposed for the landmark nodes in the pose-graph to store object position, orientation and size/scale. The proposed formulation is general and it can be applied to different geometries; in this paper we focus on indoor environments where human-made artifacts commonly share a planar rectangular shape, e.g., windows, doors, cabinets, etc. The approach can be easily extended to urban scenarios where similar shapes exists as well. Experiments in simulation show good performance, particularly in object geometry reconstruction.
