ADABOOST GPU-based classifier for direct volume rendering

Oscar Amoros*, Sergio Escalera, Anna Puig

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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.

Original languageEnglish
Title of host publicationGRAPP 2011 - Proceedings of the International Conference on Computer Graphics Theory and Applications
Number of pages5
Publication date2011
Pages215-219
ISBN (Print)9789898425454
Publication statusPublished - 2011
Externally publishedYes
EventInternational Conference on Computer Graphics Theory and Applications, GRAPP 2011 - Vilamoura, Algarve, Portugal
Duration: 5 Mar 20117 Mar 2011

Conference

ConferenceInternational Conference on Computer Graphics Theory and Applications, GRAPP 2011
Country/TerritoryPortugal
CityVilamoura, Algarve
Period05/03/201107/03/2011
SponsorInst. Syst. Technol. Inf., Control Commun. (INSTICC)
SeriesGRAPP 2011 - Proceedings of the International Conference on Computer Graphics Theory and Applications

Keywords

  • Computing and parallel rendering
  • High-performance
  • Rendering hardware
  • Volume rendering

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