Hidden Markov models : applications in computer vision

Description

Hidden Markov models (HMMs) originally emerged in the domain of speech recognition. In recent years, they have attracted growing interest in the area of computer vision as well. This book is a collection of articles on new developments in the theory of HMMs and their application in computer vision. It addresses topics such as handwriting recognition, shape recognition, face and gesture recognition, tracking, and image database retrieval. This book is also published as a special issue of the International Journal of Pattern Recognition and Artificial Intelligence (February 2001).  Read more... Preface / H. Bunke and T. Caelli -- Introduction: A simple complex in artificial intelligence and machine learning / B. H. Juang -- An introduction to hidden Markov models and Bayesian networks / Z. Ghahramani -- Multilingual 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 & H. Bunke -- A 2-D HMM method for offline handwritten character recognition / H.-S. Park ... [et al.] -- Data-driven design of HMM topology for online handwriting recognition / J. J. Lee, J. Kim & J. H. Kim -- Hidden Markov models for modeling and recognizing gesture under variation / A. D. Wilson & A. F. Bobick -- Sentence lipreading using hidden Markov model with integrated grammar / K. Yu, X. Jiang & H. Bunke -- Tracking and surveillance in wide-area spatial environments using the abstract hidden Markov model / H. H. Bui, S. Venkatesh & G. West -- Shape tracking and production using hidden Markov models / T. Caelli, A. McCabe & G. Briscoe -- An integrated approach to shape and color-based image retrieval of rotated objects using hidden Markov models / S. Milller, S. Eickeler & G. Rigoll.