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.

翻译：在本文中,我们提出了一个基于目标级SLAM系统的新规模估算方法。为了获得重建后的地图的绝对规模,我们得出一种非线性优化方法,使符合其体积分布的物体的规模与实际世界的大小,而不必依赖任何先前的重力方向信息。我们采用了双四制来代表物体,使其能紧凑和准确地适应物体。在拟议的单级物体级SLAM系统中,基于二维探测和定向装订的捆绑框的限制,两四制快速初始化,并进一步优化,以便为规模估算提供可靠的尺寸。