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Pose estimation and tracking using multivariate regression
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DOI：10.1016/j.patrec.2008.02.004.png)
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Abstract
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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 one-to-many mapping from image features to state space, thereby being able to handle pose ambiguity. (c) 2008 Elsevier B.V. All rights reserved.
Keywords:
regression
relevance vector machines
tracking
articulated motion
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