Accurate Non-Iterative O(n) Solution to the PnP Problem

By Francesc Moreno-Noguer, Vincent Lepetit, Pascal Fua. IEEE International Conference on Computer Vision, 2007

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Evaluation of Interest Point Detectors and Feature Descriptors for Visual Tracking (2011, background): “(Moreno-Noguer et al. 2007), RANSAC = random sample consensus (Fischler and Bolles 1981), SSD = sum of squared distances, UKF = Unscented Kalman Filter (Julier and Uhlmann 1997)”
Multiple 3D Object tracking for augmented reality (2008, methodology): “Since some of these correspondences can be erroneous, the object pose is estimated using RANSAC and a non-iterative P-n-P algorithm [6].”
Vision-Based Pose Estimation From Points With Unknown Correspondences (2014, methodology): “(2) Non-iterative methods: equations are formulated between object points and their images, in which the depths of points are eliminated, and the camera pose is estimated from the equations [3], [11]–[15].”