Interactive multi-label segmentation

Authors:
Jakob Santner;Thomas Pock;Horst Bischof
Affiliations:
Institute of Computer Graphics and Vision, Graz University of Technology, Austria;Institute of Computer Graphics and Vision, Graz University of Technology, Austria;Institute of Computer Graphics and Vision, Graz University of Technology, Austria
Venue:
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Year:
2010

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Abstract

This paper addresses the problem of interactive multilabel segmentation. We propose a powerful new framework using several color models and texture descriptors, Random Forest likelihood estimation as well as a multi-label Potts-model segmentation. We perform most of the calculations on the GPU and reach runtimes of less than two seconds, allowing for convenient user interaction. Due to the lack of an interactive multi-label segmentation benchmark, we also introduce a large publicly available dataset. We demonstrate the quality of our framework with many examples and experiments using this benchmark dataset.