Overview

Motion-based recognition deals with the recognition of an object and/or its motion, based on motion in a series of images. In this approach, a sequence containing a large number of frames is used to extract motion information. The advantage is that a longer sequence leads to recognition of higher level motions, like walking or running, which consist of a complex and co-ordinated series of events. Unlike much previous research in motion, this approach does not require explicit reconstruction of shape from the images prior to recognition. This book provides a state-of-the-art study of this rapidly developing discipline. It consists of a collection of invited chapters by researchers throughout the world covering various aspects of motion-based recognition including lipreading, gesture recognition, facial expression recognition, gait analysis, cyclic motion detection, and activity recognition. This volume should be of interest to researchers and postgraduate students whose work involves computer vision, robotics and image processing.

Full Product Details

Author:   Mubarak Shah ,  Ramesh Jain
Publisher:   Springer
Imprint:   Springer
Edition:   1997 ed.
Volume:   9
Dimensions:   Width: 15.60cm , Height: 2.20cm , Length: 23.40cm
Weight:   1.590kg
ISBN:  

9780792346180

ISBN 10:   0792346181
Pages:   374
Publication Date:   31 July 1997
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of print, replaced by POD  
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Table of Contents

1 Visual Recognition of Activities, Gestures, Facial Expressions and Speech: An Introduction and a Perspective.- I Human Activity Recognition.- 2 Estimating Image Motion Using Temporal Multi-Scale Models of Flow and Acceleration.- 3 Learning Reformable Models for Tracking the Human Body.- 4 Cyclic Motion Analysis Using the Period Trace.- 5 Temporal Texture and Activity Recognition.- 6 Action Recognition Using Temporal Templates.- 7 Human Activity Recognition.- 8 Human Movement Analysis Based on Explicit Motion Models.- II Gesture Recognition and Facial Expression Recognition.- 9 State-Based Recognition of Gesture.- 10 Real-Time American Sign Language Recognition from Video Using Hidden Markov Models.- 11 Recognizing Human Motion Using Parameterized Models of Optical Flow.- 12 Facial Expression Recognition Using Image Motion.- III Lipreading.- 13 Learning Visual Models for Lipreading.- 14 Continuous Automatic Speech Recognition by Lipreading.- 15 Visually Recognizing Speech Using Eigensequences.

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