Ground Plane based Absolute Scale Estimation for Monocular Visual Odometry
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Abstract (arXiv)
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.
Key facts. Cited by 10 papers in the map (data through 13 Oct 2026). First posted on arXiv 3 Mar 2019.
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Citing papers per year: 2021: 4; 2022: 3; 2023: 0; 2024: 0; 2025: 1; 2026: 2.
10 papers.
- 2021DF-VO: What Should Be Learnt for Visual Odometry?cited by 22
- 2022Dense Prediction Transformer for Scale Estimation in Monocular Visual Odometrycited by 6
- 2021Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometrycited by 5
- 2021Improved Real-Time Monocular SLAM Using Semantic Segmentation on Selective Framescited by 5
- 2021Learning Interpretable BEV Based VIO without Deep Neural Networkscited by 2
- 2022Towards Accurate Ground Plane Normal Estimation from Ego-Motioncited by 2
- 2022A high-precision self-supervised monocular visual odometry in foggy weather based on robust cycled generative adversarial networks and multi-task learning aided depth estimationcited by 1
- 2026VGGT-Align: Bridging Local Reconstruction and Global Consistency for Long-Sequence 3D Reconstructioncited by 1
- 2025Geometry-Constrained Monocular Scale Estimation Using Semantic Segmentation for Dynamic Scenescited by 0
- 2026DP-SfM: Dual-Pixel Structure-from-Motion without Scale Ambiguitycited by 0
- 2026VGGT-Align: Bridging Local Reconstruction and Global Consistency for Long-Sequence 3D Reconstruction15 Aug 2026
- 2026DP-SfM: Dual-Pixel Structure-from-Motion without Scale Ambiguity3 May 2026
- 2025Geometry-Constrained Monocular Scale Estimation Using Semantic Segmentation for Dynamic Scenes6 Mar 2025
- 2022Towards Accurate Ground Plane Normal Estimation from Ego-Motion8 Dec 2022
- 2022Dense Prediction Transformer for Scale Estimation in Monocular Visual Odometry4 Oct 2022
- 2022A high-precision self-supervised monocular visual odometry in foggy weather based on robust cycled generative adversarial networks and multi-task learning aided depth estimation9 Mar 2022
- 2021Learning Interpretable BEV Based VIO without Deep Neural Networks25 Sep 2021
- 2021Improved Real-Time Monocular SLAM Using Semantic Segmentation on Selective Frames30 Apr 2021
- 2021DF-VO: What Should Be Learnt for Visual Odometry?1 Mar 2021
- 2021Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry15 Jan 2021