We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
We describe a method of representing human activities that allows a collection of motions to be queried without examples, using a simple and effective query language. Our approach...
This paper presents a learning based approach to tracking articulated human body motion from a single camera. In order to address the problem of pose ambiguity, a one-to-many mappi...
Motion and interaction with the environment are fundamentally
intertwined. Few people-tracking algorithms exploit
such interactions, and those that do assume that surface
geomet...
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 a...