The detection and tracking of three-dimensional human body models has progressed rapidly but successful approaches typically rely on accurate foreground silhouettes obtained using...
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...
We present a vision system for the 3-D modelbased tracking of unconstrained human movement. Using image sequences acquired simultaneously from multiple views, we recover the 3-D b...
Today many applications routinely generate large quantities of data. The data often takes the form of (time) series, or more generally streams, i.e. an ordered sequence of records...
Abstract. Hidden Markov models are traditionally decoded by the Viterbi algorithm which finds the highest probability state path in the model. In recent years, several limitations ...