How to turn your camera into a perfect pinhole model
Ivan De Boi, Stuti Pathak, Marina Oliveira, Rudi Penne

TL;DR
This paper introduces a novel Gaussian process-based pre-processing technique that removes distortions from images, enabling accurate camera calibration without assuming specific distortion models, even in severely warped images.
Contribution
We propose a new method that constructs a virtual ideal pinhole camera using Gaussian processes, simplifying calibration and removing distortions without iterative optimization.
Findings
Effective distortion removal in severely warped images
Simplified calibration with fewer parameters
Validated on synthetic and real images
Abstract
Camera calibration is a first and fundamental step in various computer vision applications. Despite being an active field of research, Zhang's method remains widely used for camera calibration due to its implementation in popular toolboxes. However, this method initially assumes a pinhole model with oversimplified distortion models. In this work, we propose a novel approach that involves a pre-processing step to remove distortions from images by means of Gaussian processes. Our method does not need to assume any distortion model and can be applied to severely warped images, even in the case of multiple distortion sources, e.g., a fisheye image of a curved mirror reflection. The Gaussian processes capture all distortions and camera imperfections, resulting in virtual images as though taken by an ideal pinhole camera with square pixels. Furthermore, this ideal GP-camera only needs one…
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Taxonomy
TopicsAdvanced Vision and Imaging · Optical measurement and interference techniques · Image Processing Techniques and Applications
