Sensor-based statistical models promise to support a variety of advances in human-computer interaction, but building applications that use them is currently difficult and potentia...
Bayesian networks are an attractive modeling tool for human sensing, as they combine an intuitive graphical representation with ef?cient algorithms for inference and learning. Ear...
Tanzeem Choudhury, James M. Rehg, Vladimir Pavlovi...
Modern machine learning techniques provide robust approaches for data-driven modeling and critical information extraction, while human experts hold the advantage of possessing hig...
Background: The availability of complete genomic sequences for hundreds of organisms promises to make obtaining genome-wide estimates of substitution rates, selective constraints ...
Amy Egan, Anup Mahurkar, Jonathan Crabtree, Jonath...
In recent years 3D virtual characters have become more common in desktop interfaces, particularly in gaming and entertainment applications. In this paper we describe how augmented...
Daniel Wagner, Mark Billinghurst, Dieter Schmalsti...