We consider the problem of computing the likelihood of a gesture from regular, unaided video sequences, without relying on perfect segmentation of the scene. Instead of requiring ...
We propose a novel statistical approach to detect defects in digitized archive film by using temporal information across a number of frames modeled with an HMM. The HMM is traine...
The problem of prediction future event given an individual sequence of past events is considered. Predictions are given in form of real numbers pn which are computed by some algori...
This paper presents an extensive evaluation, on artificial datasets, of EDY, an unsupervised algorithm for automatically synthesizing a Structured Hidden Markov Model (S-HMM) from ...
The hierarchical hidden Markov model (HHMM) is a generalization of the hidden Markov model (HMM) that models sequences with structure at many length/time scales [FST98]. Unfortuna...