Growing Regression Forests by Classification: Applications to Object Pose Estimation

22 Dec 2013 Kota Hara Rama Chellappa

In this work, we propose a novel node splitting method for regression trees and incorporate it into the regression forest framework. Unlike traditional binary splitting, where the splitting rule is selected from a predefined set of binary splitting rules via trial-and-error, the proposed node splitting method first finds clusters of the training data which at least locally minimize the empirical loss without considering the input space... (read more)

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