Almost all successful machine learning algorithms and cognitive models require powerful representations capturing the features that are relevant to a particular problem. We draw o...
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
We present a fully automatic method for content selection evaluation in summarization that does not require the creation of human model summaries. Our work capitalizes on the assu...
In this paper, we propose a human daily activity recognition method by fusing the data from two wearable inertial sensors attached on one foot and the waist of the human subject, r...
Abstract— We propose a system for human computer interaction via 3D hand movements, based on a combination of visual tracking and a cheap, off-the-shelf, accelerometer. We use a ...