A Robust Roll Angle Estimation Algorithm Based on Gradient Descent

Fan, Rui; Wang, Lujia; Liu, Ming; Pitas, Ioannis

doi:10.23919/eusipco.2019.8903049

Cited by 4 publications

(2 citation statements)

References 27 publications

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“…Therefore, we are planning to leverage inertial measurements and visual-inertial coupling for a more robust visual odometry system. Furthermore, we plan to use our recently published work [28] to provide the UAV with the roll angle information. We believe this can further improve the odometry accuracy.…”

Section: Discussionmentioning

confidence: 99%

A Robust Pavement Mapping System Based on Normal-Constrained Stereo Visual Odometry

Huang

Fan

Zhu

et al. 2019

2019 IEEE International Conference on Imaging Systems and Techniques (IST)

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Pavement condition is crucial for civil infrastructure maintenance. This task usually requires efficient road damage localization, which can be accomplished by the visual odometry system embedded in unmanned aerial vehicles (UAVs). However, the state-of-the-art visual odometry and mapping methods suffer from large drift under the degeneration of the scene structure. To alleviate this issue, we integrate normal constraints into the visual odometry process, which greatly helps to avoid large drift. By parameterizing the normal vector on the tangential plane, the normal factors are coupled with traditional reprojection factors in the pose optimization procedure. The experimental results demonstrate the effectiveness of the proposed system. The overall absolute trajectory error is improved by approximately 20%, which indicates that the estimated trajectory is much more accurate than that obtained using other state-of-the-art methods.

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Section: Discussionmentioning

confidence: 99%

A Robust Pavement Mapping System Based on Normal-Constrained Stereo Visual Odometry

Huang

Fan

Zhu

et al. 2019

2019 IEEE International Conference on Imaging Systems and Techniques (IST)

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“…(2) was solved using gradient descent algorithm [66]. In 2019, [53] proves that (2) has a closed-form solution 1 as follows [53]:…”

Section: Traditional Image Analysis-based Approachesmentioning

confidence: 99%

Computer-Aided Road Inspection: Systems and Algorithms

Fan¹,

Guo²,

Wang³

et al. 2022

Preprint

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Road damage is an inconvenience and a safety hazard, severely affecting vehicle condition, driving comfort, and traffic safety. The traditional manual visual road inspection process is pricey, dangerous, exhausting, and cumbersome. Also, manual road inspection results are qualitative and subjective, as they depend entirely on the inspector's personal experience. Therefore, there is an ever-increasing need for automated road inspection systems. This chapter first compares the five most common road damage types. Then, 2-D/3-D road imaging systems are discussed. Finally, state-of-the-art machine vision and intelligence-based road damage detection algorithms are introduced.

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