  Hidden Markov models with observations in a Euclidean space play an important
role in signal and image processing. Previous work extending to models where
observations lie in Riemannian manifolds based on the Baum-Welch algorithm
suffered from high memory usage and slow speed. Here we present an algorithm
that is online, more accurate, and offers dramatic improvements in speed and
efficiency.
