Solving the perspective-three-point problem with linear combinations: An accurate and efficient method

Yu, Qida; Xu, Guili; Dong, Wende; Wang, Zhengsheng

doi:10.1016/j.ijleo.2020.165740

Cited by 3 publications

(1 citation statement)

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“…For example, Zhou [17] proposed an efficient PnP solution using an uncalibrated camera of unknown focal length. Yu [18] presented an efficient algebraic solution to the perspective 3-point problem in which the camera pose was estimated from three given 3D-2D correspondence sets. Zhou [19], however, estimated the camera pose using n ≥ 3 2D-3D line correspondences.…”

Section: Pnp Problemmentioning

confidence: 99%

Heuristic EPnP-Based Pose Estimation for Underground Machine Tracking

Zheng

Song

et al. 2022

Symmetry

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Pose estimation is one of the most complicated and compromising problems for underground mining machine tracking, and it is particularly important for hydraulic support autonomous following mining machine (AFM) policy-making system. In this paper, a low-cost infrared vision-based system through an Efficient Perspective-n-Point (EPnP) algorithm is proposed. To improve efficiency and simplify computation, a traditional EPnP algorithm is modified through a nature-inspired heuristic optimization algorithm. The optimized algorithm is integrated into the AFM policy-making system to estimate the relative pose (R-Pose) estimation between hydraulic support and the mining machine’s shearer drum. Simple yet effective numerical simulations and industrial experiments were carried out to validate the proposed method. The pose estimation error was ≤1% under normal lighting and illuminance, and ≤2% in a simulated underground environment, which was accurate enough to meet the needs of practical applications. Both numerical simulation and industrial experiment proved the superiority of the approach.

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Section: Pnp Problemmentioning

confidence: 99%