论文标题
单眼对象的双尺度估计量
Scale Estimation with Dual Quadrics for Monocular Object SLAM
论文作者
论文摘要
刻度歧义问题本质上是单眼大满贯无法解决的，而没有移动相机之间的度量基线。在本文中，我们提出了一种基于对象级别SLAM系统的新型量表估计方法。为了获得重建图的绝对尺度，我们得出了一种非线性优化方法，以使对象的缩放尺寸符合物理世界中其大小的分布，而无需依赖任何先前的重力方向信息。我们采用双二极管来表示对象紧凑，准确地拟合对象的能力。在提出的单眼对象级数系统系统中，双四四轴是基于2-D检测和拟合面向边界框的约束而迅速初始化的，并得到了进一步优化以提供可靠的尺寸以进行规模估计。
The scale ambiguity problem is inherently unsolvable to monocular SLAM without the metric baseline between moving cameras. In this paper, we present a novel scale estimation approach based on an object-level SLAM system. To obtain the absolute scale of the reconstructed map, we derive a nonlinear optimization method to make the scaled dimensions of objects conforming to the distribution of their sizes in the physical world, without relying on any prior information of gravity direction. We adopt the dual quadric to represent objects for its ability to fit objects compactly and accurately. In the proposed monocular object-level SLAM system, dual quadrics are fastly initialized based on constraints of 2-D detections and fitted oriented bounding box and are further optimized to provide reliable dimensions for scale estimation.
