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dc.contributor.authorGrau, Sergien_US
dc.contributor.authorPuig, Annaen_US
dc.contributor.authorEscalera, Sergioen_US
dc.contributor.authorSalamó, Mariaen_US
dc.contributor.editorBruno Levy and Xin Tong and KangKang Yinen_US
dc.date.accessioned2014-01-27T18:18:12Z
dc.date.available2014-01-27T18:18:12Z
dc.date.issued2013en_US
dc.identifier.isbn978-3-905674-50-7en_US
dc.identifier.urihttp://dx.doi.org/10.2312/PE.PG.PG2013short.023-028en_US
dc.description.abstractThis paper defines an intelligent and interactive framework to classify multiple regions of interest from the original data on demand, without requiring any preprocessing or previous segmentation. The proposed intelligent and interactive approach is divided in three stages: visualize, training and testing. First, users visualize and label some samples directly on slices of the volume. Training and testing are based on a framework of Error Correcting Output Codes and Adaboost classifiers that learn to classify each region the user has painted. Later, at the testing stage, each classifier is directly applied on the rest of samples and combined to perform multi-class labeling, being used in the final rendering. We also parallelized the training stage using a GPU-based implementation for obtaining a rapid interaction and classification.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.5 [Computer Graphics]en_US
dc.subjectComputational Geometry and Object Modelingen_US
dc.subjectObject hierarchiesen_US
dc.titleIntelligent Interactive Volume Classificationen_US
dc.description.seriesinformationPacific Graphics Short Papersen_US


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