2013 ICCV ICCV 2013

Unsupervised Intrinsic Calibration from a Single Frame Using a "Plumb-Line" Approach

Abstract

Estimating the amount and center of distortion from lines in the scene has been addressed in the literature by the socalled "plumb-line" approach. In this paper we propose a new geometric method to estimate not only the distortion parameters but the entire camera calibration (up to an "angular" scale factor) using a minimum of 3 lines. We propose a new framework for the unsupervised simultaneous detection of natural image of lines and camera parameters estimation, enabling a robust calibration from a single image. Comparative experiments with existing automatic approaches for the distortion estimation and with ground truth data are presented.

🚀 Conference Pioneer — ICCV 2013
🧭 Keyword Pioneer — distortion estimation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics