Illuminant Estimation using Ensembles of Multivariate Regression Trees

Illuminant Estimation using Ensembles of Multivariate Regression Trees

White balancing is a fundamental step in the image processing pipeline. The process involves estimating the chromaticity of the illuminant or light source and using the estimate to correct the image to remove any color cast. Given the importance of the problem, there has been much previous work on illuminant estimation. Recently, an approach based on ensembles of univariate regression trees tha...

Multivariate Regression Trees

Pose estimation and tracking using multivariate regression

This paper presents an extension of the relevance vector machine (RVM) algorithm to multivariate regression. This allows the application to the task of estimating the pose of an articulated object from a single camera. RVMs are used to learn a oneto-many mapping from image features to state space, thereby being able to handle pose ambiguity.

Efficient Multivariate Quantile Regression Estimation

We propose an efficient semiparametric estimator for the multivariate linear quantile regression model in which the conditional joint distribution of errors given regressors is unknown. The procedure can be used to estimate multiple conditional quantiles of the same regression relationship. The proposed estimator is asymptotically as efficient as if the conditional distribution were known. Simu...

Permutation Testing in Multivariate Regression Trees

Formal testing procedures are generally not available for determining which splits in a regression tree are significant. Such a procedure is presented using permutation testing applied to order statistics. Finally, traditional cross validation and the permutation testing procedure are compared in a specific example.