A Consistently Fast and Globally Optimal Solution to the Perspective-n-Point Problem

Terzakis, George; Lourakis, Manolis

doi:10.1007/978-3-030-58452-8_28

Cited by 68 publications

(23 citation statements)

References 47 publications

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“…Once the initial place is retrieved, our method proceeds with the actual 6-DoF localization, which is based on a Perspective-n-Point (PnP) solver [43]. The goal is to find the camera pose that, given a set of 3D points, minimizes the reprojection error of the 2D points in the camera plane.…”

Section: -Dof Visual Localizationmentioning

confidence: 99%

Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization

Vallone¹,

Warburg²,

Hansen³

et al. 2022

Preprint

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Place recognition and visual localization are particularly challenging in wide baseline configurations. In this paper, we contribute with the Danish Airs and Grounds (DAG) dataset, a large collection of street-level and aerial images targeting such cases. Its main challenge lies in the extreme viewing-angle difference between query and reference images with consequent changes in illumination and perspective. The dataset is larger and more diverse than current publicly available data, including more than 50 km of road in urban, suburban and rural areas. All images are associated with accurate 6-DoF metadata that allows the benchmarking of visual localization methods.We also propose a map-to-image re-localization pipeline, that first estimates a dense 3D reconstruction from the aerial images and then matches query street-level images to street-level renderings of the 3D model. The dataset can be downloaded at: https://frederikwarburg.github.io/DAG/.

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Section: -Dof Visual Localizationmentioning

confidence: 99%

Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization

Vallone¹,

Warburg²,

Hansen³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The method is thus based on finding the point where the transformation is best estimated and using only this local information to constrain the pose. The SQPnP (sequential quadratic PnP) algorithm [74] formulates the PnP problem as a nonlinear quadratic program and identifies regions in the parameter space that contain unique minima. This guarantees that at least one of them is the global minimum.…”

Section: Pnp Algorithmsmentioning

confidence: 99%

High-Precision Absolute Pose Sensing for Parallel Mechanisms

Schempp

Schulz

2022

Sensors

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A parallel mechanism’s pose is usually obtained indirectly from the active joints’ coordinates by solving the direct kinematics problem. Its accuracy mainly depends on the accuracy of the measured active joints’ coordinates, the tolerances in the active and passive joints, possible backlash, axes misalignment, limb deformations due to stress or temperature, the initial pose estimate that is used for the numerical method, and the accuracy of the kinematic model itself. Backlash and temperature deformations in the active joints especially hinder high-precision applications as they usually cannot be observed. By implementing a camera module on the base platform and an array of fiducial tags on the moveable manipulator platform of a parallel mechanism, a highly accurate, direct, and absolute pose measurement system can be obtained that can overcome those limitations. In this paper, such a measurement system is proposed, designed, and its accuracy is investigated on a state-of-the-art H-811.I2 6-axis miniature hexapod by Physik Instrumente (PI) GmbH & Co. KG.

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“…There has been sufficient research on the design, detection, and decoding processes of visual fiducial markers, such as ARTag [15], ArUco 3 [16], and AprilTag 3 [17]. For tag-based pose estimation problem, also named as Solve Pose from n Points (SolvePnP) problem, many algorithms have been proposed and integrated into the OpenCV library, such as EPnP [18], IPPE [19], and SQPnP [20]. The motivation is to design an inexpensive localization method for indoor AR robotics systems, and hence the tag-based approach is chosen in this work.…”

Section: Related Workmentioning

confidence: 99%

Indoor Localization for Quadrotors using Invisible Projected Tags

Li¹,

Liu²,

Zhang³

2022

Preprint

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Augmented reality (AR) technology has been introduced into the robotics field to narrow the visual gap between indoor and outdoor environments. However, without signals from satellite navigation systems, flight experiments in these indoor AR scenarios need other accurate localization approaches. This work proposes a real-time centimeter-level indoor localization method based on psycho-visually invisible projected tags (IPT), requiring a projector as the sender and quadrotors with high-speed cameras as the receiver. The method includes a modulation process for the sender, as well as demodulation and pose estimation steps for the receiver, where screen-camera communication technology is applied to hide fiducial tags using human vision property. Experiments have demonstrated that IPT can achieve accuracy within ten centimeters and a speed of about ten FPS. Compared with other localization methods for AR robotics platforms, IPT is affordable by using only a projector and high-speed cameras as hardware consumption and convenient by omitting a coordinate alignment step. To the authors' best knowledge, this is the first time screen-camera communication is utilized for AR robot localization.

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A Consistently Fast and Globally Optimal Solution to the Perspective-n-Point Problem

Cited by 68 publications

References 47 publications

Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization

Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization

High-Precision Absolute Pose Sensing for Parallel Mechanisms

Indoor Localization for Quadrotors using Invisible Projected Tags

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