We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
Abstract. We introduce the use of appearance-based features, and tangent distance or the image distortion model to account for image variability within the hidden Markov model emis...
Philippe Dreuw, Daniel Keysers, Thomas Deselaers, ...
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
We describe a new algorithm for protein classi cation and the detection of remote homologs. The rationale is to exploit both vertical and horizontal information of a multiple alig...
In this paper, we present a novel approach for human action recognition with histograms of 3D joint locations (HOJ3D) as a compact representation of postures. We extract the 3D sk...