loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

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

Affiliation: University of Bonn, Germany

ISBN: 978-989-758-090-1

ISSN: 2184-4321

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.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 35.168.111.204

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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 - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-090-1, ISSN 2184-4321, 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 - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={156-164},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005316201560164},
isbn={978-989-758-090-1},
}

TY - CONF

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

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.