A collection of articles on developments in the theory of hidden Markov models and their application in computer vision. It addresses topics such as handwriting recognition, shape recognition, face and gesture recognition, tracking, and image database retrieval.

Introduction - a simple complex in artificial intelligence and machine learning, B.H. Juang; an introduction to hidden Markov models and Bayesian networks, Z. Chahramani; multi-lingual machine printed OCR, P. Natarajan et al; using a statistical language model to improve the performance of an HMM-based cursive handwriting recognition system, U.-V. Marti and H. Bunke; a 2-D HMM method for offline handwritten character recognition, H.-S. Park et al; data-driven design for HMM topology for online handwriting recognition, J.J. Lee et al; hidden Markov models for modelling and recognizing gesture under variation, A.D. Wilson and A.F. Bobick; sentence lipreading using hidden Markov model with integrated grammar, K. Yu et al; tracking and surveillance in wide-area spatial environments using the abstract hidden Markov model, H.H. Bui et al; shape tracking and production using hidden Markov models, T. Caelli et al; an integrated approach to shape and colour-based image retrieval of rotated objects using hidden Markov models, S. Muller et al.