We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
— The demand for flexible and re-programmable robots has increased the need for programming by demonstration systems. In this paper, grasp recognition is considered in a program...
In this work a Gaussian Hidden Markov Model (GHMM) based automatic sign language recognition system is built on the SIGNUM database. The system is trained on appearance-based feat...
This paper proposes a novel handwriting recognition interface for wearable computing where users write characters continuously without pauses on a small single writing box. Since ...