2013 CVPR CVPR 2013

Rolling Shutter Camera Calibration

Abstract

Rolling Shutter (RS) cameras are used across a wide range of consumer electronic devices--from smart-phones to high-end cameras. It is well known, that if a RS camera is used with a moving camera or scene, significant image distortions are introduced. The quality or even success of structure from motion on rolling shutter images requires the usual intrinsic parameters such as focal length and distortion coefficients as well as accurate modelling of the shutter timing. The current state-of-the-art technique for calibrating the shutter timings requires specialised hardware. We present a new method that only requires video of a known calibration pattern. Experimental results on over 60 real datasets show that our method is more accurate than the current state of the art.

🚀 Conference Pioneer — CVPR 2013
🌉 Interdisciplinary Bridge — Computer Vision and Machine Learning
🧭 Keyword Pioneer — intrinsic parameter
🐣 Hot Topic Early Bird — structure from motion
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Reinforcement Learning, Robotics