Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images

Abstract

We address the problem of estimating human body pose from a single image with cluttered background. We train multiple local linear regressors for estimating the 3D pose from a feature vector of gradient orientation histograms. Each linear regressor is capable of selecting relevant components of the feature vector depending on pose by training it on a pose… (More)
DOI: 10.1007/978-3-540-88688-4_32

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@inproceedings{Okada2008RelevantFS, title={Relevant Feature Selection for Human Pose Estimation and Localization in Cluttered Images}, author={Ryuzo Okada and Stefano Soatto}, booktitle={ECCV}, year={2008} }