Hidden Markov Models

Applications In Computer Vision

By: Horst Bunke (Editor), Terry Michael Caelli (Editor)

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Hardcover | 7 June 2001

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Hardcover
244 Pages

Dimensions(cm)
26.04 x 16.51 x 1.91

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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.

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Non-Fiction Medicine Medicine in General Computing & I.T.Computer Science Artificial Intelligence Computer Vision Mathematics Applied Mathematics Mathematical Modelling Systems Analysis & Design Booktopia Publisher Services

World Scientific Publishing

Preface	p. 1
Introduction: A Simple Complex in Artificial Intelligence and Machine Learning	p. 5
An Introduction to Hidden Markov Models and Bayesian Networks	p. 9
Multilingual Machine Printed OCR	p. 43
Using a Statistical Language Model to Improve the Performance of an HMM-Based Cursive Handwriting Recognition System	p. 65
A 2-D HMM Method for Offline Handwritten Character Recognition	p. 91
Data-Driven Design of HMM Topology for Online Handwriting Recognition	p. 107
Hidden Markov Models for Modeling and Recognizing Gesture Under Variation	p. 123
Sentence Lipreading Using Hidden Markov Model with Integrated Grammar	p. 161
Tracking and Surveillance in Wide-Area Spatial Environments Using the Abstract Hidden Markov Model	p. 177
Shape Tracking and Production Using Hidden Markov Models	p. 197
An Integrated Approach to Shape and Color-Based Image Retrieval of Rotated Objects Using Hidden Markov Models	p. 223
Table of Contents provided by Blackwell. All Rights Reserved.

Hidden Markov Models

Applications In Computer Vision

At a Glance

Hardcover

Shipping

How to return your order

Defective items

You Can Find This Book In

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