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...
Methods for super-resolution can be broadly classified
into two families of methods: (i) The classical multi-image
super-resolution (combining images obtained at subpixel
misali...
Methods for super-resolution (SR) can be broadly classified into two families of methods: (i) The classical multi-image super-resolution (combining images obtained at subpixel misa...
We propose Action-Reaction Learning as an approach for analyzing and synthesizing human behaviour. This paradigm uncovers causal mappings between past and future events or between...
Emerging ubiquitous and pervasive computing applications often need to know where things are physically located. To meet this need, many locationsensing systems have been develope...