Simulating Kinect Noise: adding noise to clean depth-maps rendered with a graphics engine. This is a part of the ICL-NUIM dataset. The depth noise is modelled as a combination of the noise models used in Barraon et al. 2013 and Bohg et al. 2014 as referenced below.
python add_noise.py
The left image is a sample depth image from a simulator and the right image is the depth image with noise added to it.
If you use this code, please consider citing the following papers
@article{handa:etal:2014,
title = {A benchmark for RGB-D visual odometry, 3D reconstruction and SLAM},
author = {Handa, Ankur and Whelan, Thomas and McDonald, John and Davison, Andrew J},
journal = {ICRA},
year = {2014},
}
@article{Barron:etal:2013A,
author = {Jonathan T. Barron and Jitendra Malik},
title = {Intrinsic Scene Properties from a Single RGB-D Image},
journal = {CVPR},
year = {2013},
}
@article{Bohg:etal:2014,
title = {Robot arm pose estimation through pixel-wise part classification},
author = {Bohg, Jeannette and Romero, Javier and Herzog, Alexander and Schaal, Stefan},
journal = {ICRA},
year = {2014},
}
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