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Keyframe-based Photometric Online Calibration and Color Correction

251 views · Published 12 August 2018 · 3:16 · Indexed 5 October 2026

Channel: nimbro · 2018 · Science & Technology

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Video attachement for  Jan Quenzel, Jannis Horn, Sebastian Houben, Sven Behnke :
"Keyframe-based Photometric Online Calibration and Color Correction"
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
http://www.ais.uni-bonn.de/papers/IROS_2018_Quenzel.pdf

Abstract: 
Finding the parameters of a vignetting function
for a camera currently involves the acquisition of several images
in a given scene under very controlled lighting conditions, a
cumbersome and error-prone task where the end result can only
be confirmed visually. Many computer vision algorithms assume
photoconsistency, constant intensity between scene points in
different images, and tend to perform poorly if this assumption
is violated. We present a real-time online vignetting and
response calibration with additional exposure estimation for
global-shutter color cameras. Our method does not require
uniformly illuminated surfaces, known texture or specific geometry.
The only assumptions are that the camera is moving,
the illumination is static and reflections are Lambertian. Our
method estimates the camera view poses by sparse visual SLAM
and models the vignetting function by a small number of thin
plate splines (TPS) together with a sixth-order polynomial to
provide a dense estimation of attenuation from sparsely sampled
scene points. The camera response function (CRF) is jointly
modeled by a TPS and a Gamma curve. We evaluate our
approach on synthetic datasets and in real-world scenarios with
reference data from a Structure-from-Motion (SfM) system. We
show clear visual improvement on textured meshes without the
need for extensive meshing algorithms. A useful calibration
is obtained from a few keyframes which makes an on-the-fly
deployment conceivable.

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