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Semantic Video Object Segmentation for Content-Based Multimedia Applications

By: Ju Guo, C.-C. Jay Kuo

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Hardcover | 30 September 2001

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Hardcover
136 Pages

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23.39 x 15.6 x 0.97

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Semantic Video Object Segmentation for Content-Based Multimedia Applications provides a thorough review of state-of-the-art techniques as well as describing several novel ideas and algorithms for semantic object extraction from image sequences. Semantic object extraction is an essential element in content-based multimedia services, such as the newly developed MPEG4 and MPEG7 standards. An interactive system called SIVOG (Smart Interactive Video Object Generation) is presented, which converts user's semantic input into a form that can be conveniently integrated with low-level video processing. Thus, high-level semantic information and low-level video features are integrated seamlessly into a smart segmentation system. A region and temporal adaptive algorithm was further proposed to improve the efficiency of the SIVOG system so that it is feasible to achieve nearly real-time video object segmentation with robust and accurate performances. Also included is an examination of the shape coding problem and the object segmentation problem simultaneously.
Semantic Video Object Segmentation for Content-Based Multimedia Applications will be of great interest to research scientists and graduate-level students working in the area of content-based multimedia representation and applications and its related fields.

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You Can Find This Book In

Non-Fiction Computing & I.T.Graphical & Digital Media Applications Digital Animation Digital Lifestyle & Online World: Consumer & User Guides Digital Video Consumer User Guides Computer Science Image Processing Medicine Medicine in General Engineering & Technology Energy Technology & Engineering

Electrical Engineering Electronics & Communications Engineering Communications Engineering & Telecommunications Television Technology Electronics Engineering Databases

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Paperback

Published: 5th November 2012

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List of Figures	p. ix
List of Tables	p. xiii
Preface	p. xv
Acknowledgments	p. xix
Introduction	p. 1
Significance of the Research	p. 1
Background of the Research	p. 2
Contributions of the Research	p. 4
Color Feature	p. 4
Automatic Segmentation Algorithm	p. 4
Interactive Semantic Object Segmentation	p. 5
Temporal and Region-adaptive Processing	p. 6
Object Shape Postprocessing	p. 6
Outline of the Monograph	p. 6
Review of Previous Work	p. 9
Change Detection	p. 9
Motion Segmentation	p. 11
Motion Model	p. 11
Previous Work in Motion Segmentation	p. 14
Spatial and Temporal Segmentation	p. 15
Spatial Segmentation Techniques	p. 15
Three Segmentation Proposals in MPEG4	p. 17
Other Combinations of Spatial and Temporal Segmentation	p. 18
User Interactive Segmentation	p. 20
Motivation	p. 20
Category of User Interaction	p. 21
Efficiency of User Interaction	p. 22
Previous Work	p. 23
Evaluation of Segmentation Quality	p. 26
Automatic Segmentation	p. 29
Video Segmentation With Color and Motion	p. 29
Color-based Spatial Segmentation	p. 31
Motion Tracking and Spatial-Temporal Integration	p. 32
Experimental Results	p. 35
Subjective Evaluation	p. 35
Objective Evaluation	p. 36
Object Shape Postprocessing	p. 45
Proposed Algorithm for Coding Optimization	p. 45
Shape Coding Optimization	p. 46
Experimental Results	p. 47
Interactive Segmentation Algorithms	p. 53
Description of the SIVOG System	p. 54
System Overview	p. 54
User Interface	p. 55
Smart-processing Kernel	p. 56
Temporal Tracking of Rigid Objects	p. 57
Boundary Update for Non-rigid Objects	p. 59
User Correction and Update	p. 63
System Evaluation	p. 64
Experimental Results	p. 64
Rigid Object Segmentation	p. 64
Non-rigid Object Segmentation	p. 66
Temporal and Spatial Adaptive Processing	p. 75
Introduction	p. 75
Description of the SIVOG System	p. 76
Semantic User Interaction	p. 76
Smart Processing kernel	p. 76
Region and Temporal Adaptive Processing	p. 79
Region Selection	p. 79
Temporal Skipping and Interpolation	p. 82
Experimental Results	p. 87
System Efficiency	p. 87
System Accuracy	p. 88
Summary and Future Work	p. 95
Future Work	p. 96
Texture Segmentation	p. 96
Model-based Segmentation Algorithm	p. 96
Object Postprocessing	p. 96
Evaluation of User's Effort	p. 97
References	p. 99
About the authors	p. 107
Index	p. 109
Table of Contents provided by Syndetics. All Rights Reserved.

Semantic Video Object Segmentation for Content-Based Multimedia Applications

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Hardcover

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