EPnP: An Accurate O(n) Solution to the PnP Problem | VitaVision
PaperInternational Journal of Computer Vision · 2009

EPnP: An Accurate O(n) Solution to the PnP Problem

Vincent LepetitFrancesc Moreno-NoguerPascal Fua
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1narrative
3registry papers cite it

In the Atlas

AlgorithmPrimary source of
EPnP: O(n) Perspective-n-Point

Non-iterative O(n) solver for the calibrated Perspective-n-Point problem: express the n reference points as weighted sums of four virtual control points, recover their camera-frame coordinates from the null space of a 12×12 matrix, and extract pose by absolute orientation.

ConceptPrimary source of
Pose Estimation

Recovery of the 6-DOF rigid transformation — rotation and translation — relating a camera to a scene, an object, or a second camera.

Cited as a reference by 1 page, grouped by domain

Features 1
Yang Parametric-Model Sub-Pixel Corner Fit

Appears in 1 narrative

NarrativeThe Geometry Pipeline Collapses

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’81’82’83’84’85’86’87’88’89’90’91’92’93’94’95’96’97’98’99’00’01’02’03’04’05’06’07’08’09’10’11’12’13’14’15’16’17’18ORB: An efficient alternative to SIFT or SURF (2011)Structure-from-Motion Revisited (2016)Sub-Pixel Chessboard Corner Localization for Camera Calibration and Pose Estimation (2018)Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography (1981)