P3P and P2P problems with known camera and object vertical directions

D’Alfonso, Luigi; Garone, Emanuele; Muraca, P.; Pugliese, Paolo

doi:10.1109/med.2013.6608760

Cited by 5 publications

(9 citation statements)

References 16 publications

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“…The present paper extends the preliminary results given in [23,24]; as in [22], we assume that both the camera and the object are equipped with IMUs, but no hypothesis on their coordinates is made. First, we face the P2P problem using inclinometers only: we prove that it admits two solutions and propose a geometrical test to mitigate the ambiguity between them.…”

Section: Pnp Problems and Imussupporting

confidence: 58%

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Camera and inertial sensor fusion for the PnP problem: algorithms and experimental results

D’Alfonso¹,

Garone

Muraca

et al. 2021

Machine Vision and Applications

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In this work, we face the problem of estimating the relative position and orientation of a camera and an object, when they are both equipped with inertial measurement units (IMUs), and the object exhibits a set of n landmark points with known coordinates (the so-called Pose estimation or PnP Problem). We present two algorithms that, fusing the information provided by the camera and the IMUs, solve the PnP problem with good accuracy. These algorithms only use the measurements given by IMUs’ inclinometers, as the magnetometers usually give inaccurate estimates of the Earth magnetic vector. The effectiveness of the proposed methods is assessed by numerical simulations and experimental tests. The results of the tests are compared with the most recent methods proposed in the literature.

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Section: Pnp Problems and Imussupporting

confidence: 58%

“…are quantities that can be computed from the measured data (see [23] for the complete expression of a, b, and c). At this point, using where…”

Section: P2p and P3p Using Accelerometers Onlymentioning

confidence: 99%

Camera and inertial sensor fusion for the PnP problem: algorithms and experimental results

D’Alfonso¹,

Garone

Muraca

et al. 2021

Machine Vision and Applications

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“…Following the lines shown in [14], the rotation matrix R can be parametrized w.r.t. the angle α representing the information usually provided by the magnetometers.…”

Section: Pnp Problem Using Accelerometers Onlymentioning

confidence: 99%

“…Most of these algorithms are iterative and require an initial guess; thus, to solve (18), an initialization value α 0 is required. A possible estimate consists of solving a P3P problem on three arbitrary chosen feature points using the P3P problem solution proposed in [14].…”

Section: Pnp Problem Using Accelerometers Onlymentioning

confidence: 99%

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On the use of IMUs in the PnP problem

D’Alfonso

Garone

Muraca

et al. 2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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In this paper the problem of estimating the relative orientation and position between a camera and an object is investigated. It is assumed that both the camera and the object are provided with an Inertial Measurement Unit (IMU) capable of measuring their attitude with respect to the gravity and the earth magnetic vectors. Furthermore, the object is assumed to contain a feature of n points, the position of which is known in the object coordinate frame. An algorithm is proposed, which uses the image provided by the camera and the information provided by the IMUs, to solve the PnP problem, i.e., to estimate the relative pose of the object in the camera reference frame. Two special cases will be studied. The first is the case where all the attitude information given by the IMU is used. In the second case only the measurements provided by inclinometers are used, neglecting those coming from the magnetometers, because they are usually quite noisy. The effectiveness of the proposed algorithms is tested either by numerical simulations and by experimental tests with cameras.E. Garone is with

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An Efficient Closed Form Solution to the Absolute Orientation Problem for Camera with Unknown Focal Length

Guo¹,

Hu²,

Zhao³

et al. 2021

Sensors

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In this paper we propose an efficient closed form solution to the absolute orientation problem for cameras with an unknown focal length, from two 2D–3D point correspondences and the camera position. The problem can be decomposed into two simple sub-problems and can be solved with angle constraints. A polynomial equation of one variable is solved to determine the focal length, and then a geometric approach is used to determine the absolute orientation. The geometric derivations are easy to understand and significantly improve performance. Rewriting the camera model with the known camera position leads to a simpler and more efficient closed form solution, and this gives a single solution, without the multi-solution phenomena of perspective-three-point (P3P) solvers. Experimental results demonstrated that our proposed method has a better performance in terms of numerical stability, noise sensitivity, and computational speed, with synthetic data and real images.

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P3P and P2P problems with known camera and object vertical directions

Cited by 5 publications

References 16 publications

Camera and inertial sensor fusion for the PnP problem: algorithms and experimental results

Camera and inertial sensor fusion for the PnP problem: algorithms and experimental results

On the use of IMUs in the PnP problem

An Efficient Closed Form Solution to the Absolute Orientation Problem for Camera with Unknown Focal Length

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