ADABOOST GPU-BASED CLASSIFIER FOR DIRECT VOLUME RENDERING

Oscar Amoros, Sergio Escalera, Anna Puig

2011

Abstract

In volume visualization, the voxel visibility and materials are carried out through an interactive editing of Transfer Function. In this paper, we present a two-level GPU-based labeling method that computes in times of rendering a set of labeled structures using the Adaboost machine learning classifier. In a pre-processing step, Adaboost trains a binary classifier from a pre-labeled dataset and, in each sample, takes into account a set of features. This binary classifier is a weighted combination of weak classifiers, which can be expressed as simple decision functions estimated on a single feature values. Then, at the testing stage, each weak classifier is independently applied on the features of a set of unlabeled samples. We propose an alternative representation of these classifiers that allow a GPU-based parallelizated testing stage embedded into the visualization pipeline. The empirical results confirm the OpenCL-based classification of biomedical datasets as a tough problem where an opportunity for further research emerges.

References

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Paper Citation


in Harvard Style

Amoros O., Escalera S. and Puig A. (2011). ADABOOST GPU-BASED CLASSIFIER FOR DIRECT VOLUME RENDERING . In Proceedings of the International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2011) ISBN 978-989-8425-45-4, pages 215-219. DOI: 10.5220/0003369902150219


in Bibtex Style

@conference{grapp11,
author={Oscar Amoros and Sergio Escalera and Anna Puig},
title={ADABOOST GPU-BASED CLASSIFIER FOR DIRECT VOLUME RENDERING},
booktitle={Proceedings of the International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2011)},
year={2011},
pages={215-219},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003369902150219},
isbn={978-989-8425-45-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2011)
TI - ADABOOST GPU-BASED CLASSIFIER FOR DIRECT VOLUME RENDERING
SN - 978-989-8425-45-4
AU - Amoros O.
AU - Escalera S.
AU - Puig A.
PY - 2011
SP - 215
EP - 219
DO - 10.5220/0003369902150219