A hierarchical semantic image labeling method via random forests

Abstract

In this paper, we propose an effective image labeling method with a hierarchical framework consists of two layers of random forests. In the first layer, random forests is performed on superpixel basis. An initial labeling map is efficiently estimated by assigning every superpixel with a unique class label. In the second layer, structured random forests is… (More)

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