This paper addresses the following question: how should we update our beliefs after observing some incomplete data, in order to make credible predictions about new, and possibly i...
This paper investigates the task of identifying frequently-used pathways from video sequences of natural outdoor scenes. Path models are adaptively learnt from the accumulation of...
We present a general, simple feature representation of sequences that allows efficient inexact matching, comparison and classification of sequential data. This approach, recently ...
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
In this paper, an analysis of the efficiency of three signal-to-noise ratio (SNR) scalable strategies for motion compensated video coders and their non-scalable counterpart is pre...
Josep Prades-Nebot, Gregory W. Cook, Edward J. Del...