CVMar 3, 2019

Ground Plane based Absolute Scale Estimation for Monocular Visual Odometry

arXiv:1903.00912v150 citations
Originality Incremental advance
AI Analysis

This addresses scale estimation for monocular camera-based systems, which is incremental as it builds on existing cues like camera height.

The paper tackles the problem of estimating absolute metric scale from a monocular camera for visual odometry, proposing a method based on ground plane and camera height that reduces scale drift, with effectiveness verified on public and self-collected image sequences.

Recovering the absolute metric scale from a monocular camera is a challenging but highly desirable problem for monocular camera-based systems. By using different kinds of cues, various approaches have been proposed for scale estimation, such as camera height, object size etc. In this paper, firstly, we summarize different kinds of scale estimation approaches. Then, we propose a robust divide and conquer the absolute scale estimation method based on the ground plane and camera height by analyzing the advantages and disadvantages of different approaches. By using the estimated scale, an effective scale correction strategy has been proposed to reduce the scale drift during the Monocular Visual Odometry (VO) estimation process. Finally, the effectiveness and robustness of the proposed method have been verified on both public and self-collected image sequences.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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