CURFIL: Random Forests for Image Labeling on GPU

Hannes Schulz; Benedikt Waldvogel; Rasha Sheikh; Sven Behnke

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Paper

CURFIL: Random Forests for Image Labeling on GPU

Topics: Machine Learning Technologies for Vision

In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, 156-164, 2015 , Berlin, Germany

Authors: Hannes Schulz ; Benedikt Waldvogel ; Rasha Sheikh and Sven Behnke

Affiliation: University of Bonn, Germany

Keyword(s): Random Forest, Computer Vision, Image Labeling, GPU, CUDA.

Abstract: Random forests are popular classifiers for computer vision tasks such as image labeling or object detection. Learning random forests on large datasets, however, is computationally demanding. Slow learning impedes model selection and scientific research on image features. We present an open-source implementation that significantly accelerates both random forest learning and prediction for image labeling of RGB-D and RGB images on GPU when compared to an optimized multi-core CPU implementation. We use the fast training to conduct hyper-parameter searches, which significantly improves on previous results on the NYU depth v2 dataset. Our prediction runs in real time at VGA resolution on a mobile GPU and has been used as data term in multiple applications.

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Paper citation in several formats:

Schulz, H.; Waldvogel, B.; Sheikh, R. and Behnke, S. (2015). CURFIL: Random Forests for Image Labeling on GPU. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP; ISBN 978-989-758-090-1; ISSN 2184-4321, SciTePress, pages 156-164. DOI: 10.5220/0005316201560164

@conference{visapp15,
author={Hannes Schulz. and Benedikt Waldvogel. and Rasha Sheikh. and Sven Behnke.},
title={CURFIL: Random Forests for Image Labeling on GPU},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP},
year={2015},
pages={156-164},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005316201560164},
isbn={978-989-758-090-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP
TI - CURFIL: Random Forests for Image Labeling on GPU
SN - 978-989-758-090-1
IS - 2184-4321
AU - Schulz, H.
AU - Waldvogel, B.
AU - Sheikh, R.
AU - Behnke, S.
PY - 2015
SP - 156
EP - 164
DO - 10.5220/0005316201560164
PB - SciTePress