Hidden Markov models : applications in computer vision
โ Scribed by Bunke, Horst; Caelli, Terry
- Publisher
- World Scientific Pub. Co.
- Year
- 2001
- Tongue
- English
- Leaves
- 246
- Series
- Series in machine perception and artificial intelligence 45.
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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 Read more...
โฆ Table of Contents
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.
โฆ Subjects
Computer vision -- Mathematical models;Markov processes;Optical pattern recognition -- Mathematical models
๐ SIMILAR VOLUMES
Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabulary continuous speech recognition (LVCSR) systems are based on HMMs. Whereas the basic principles underlying HMM-based LVCS