基于单目深度估计的半直接视觉里程计

Shuang Guo, Jifeng Guo, Chengchao Bai
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引用次数: 1

摘要

在各种视觉里程计方法中使用的各种视觉传感器中,单目相机成本低、重量轻、功耗低,更适合小型移动平台。然而,由于单目摄像机无法测量景深,因此各种单目视觉里程计或SLAM算法不可避免地存在尺度模糊的缺陷,这极大地限制了它们在现实世界中的应用。针对以上问题,本文提出了一种基于单目深度估计的半直接视觉测程算法,在半直接视觉测程中加入单目深度估计模块,为深度滤波器提供了良好的初始值。这种方法克服了尺度模糊的固有缺陷,提高了单目视觉里程测量的准确性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semi-Direct Visual Odometry Based on Monocular Depth Estimation
Among various visual sensors used in various visual odometry methods, monocular cameras are more suitable for small mobile platforms due to their low costs, light weights and low power consumptions. However, the depth of the scene cannot be measured by monocular camera so all kinds of monocular visual odometry or SLAM algorithms inevitably have the defect of scale ambiguity, which greatly limits their application in real world. To solve the above problems, a semi-direct visual odometry algorithm based on monocular depth estimation is proposed in this paper, we add a monocular depth estimation module into the semi-direct visual odometry, which provides good initial values to the depth filter. In this way, the inherent defect of scale ambiguity is overcome, and the accuracy and robustness of monocular visual odometry are improved.
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