Independent projects — infrastructure, robotics, technology surveys, and corporate research
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#OpenCV

September 18, 2026 Computer Vision Primer

PnP Primer — Recovering Camera Pose from Nothing but 3D Points and an Image

Perspective-n-Point (PnP) is the geometric problem of estimating a camera's position and orientation from known 3D points and their corresponding image points. This article works through the projection equation, P3P/AP3P, EPnP, iterative optimization, RANSAC, planar degeneracy, and how PnP is used in Visual SLAM, AR, and surveying, with the math and an implementation checklist.

September 4, 2026 Computer Vision Primer

Camera Calibration Primer — Recovering Lens Distortion and Intrinsic Parameters

Camera calibration is the process of recovering the intrinsic parameters and lens distortion needed to map pixel coordinates onto 3D space. From revisiting the pinhole model, through radial and tangential distortion models, Zhang's planar-pattern method, reprojection-error optimization, to what breaks downstream in Visual SLAM and VO when calibration drifts — a systematic walkthrough with equations and diagrams.