Online learning for automatic segmentation of 3D data

Abstract

We propose a method to perform automatic segmentation of 3D scenes based on a standard classifier, whose learning model is continuously improved by means of new samples, and a grouping stage, that enforces local consistency among classified labels. The new samples are automatically delivered to the system by a feedback loop based on a feature selection… (More)
DOI: 10.1109/IROS.2011.6094649

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