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.
List of Figures. List of Tables. Preface. Acknowledgments. 1. Introduction. 2. Review of Previous Work. 3. Automatic Segmentation. 4. Object Shape Postprocessing. 5. Interactive Segmentation Algorithms. 6. Temporal and Spatial Adaptive Processing. 7. Summary and Future Work. References. About the Authors. Index.
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.
1. Introduction.- 1. Significance of the Research.- 2. Background of the Research.- 3. Contributions of the Research.- 4. Outline of the Monograph.- 2. Review of Previous Work.- 1. Change Detection.- 2. Motion Segmentation.- 3. Spatial and Temporal Segmentation.- 4. User Interactive Segmentation.- 5. Evaluation of Segmentation Quality.- 3. Automatic Segmentation.- 1. Video Segmentation with Color and Motion.- 2. Color-based Spatial Segmentation.- 3. Motion Tracking and Spatial-Temporal Integration.- 4. Experimental Results.- 4. Object Shape Postprocessing.- 1. Proposed Algorithm for Coding Optimization.- 2. Shape Coding Optimization.- 3. Experimental Results.- 5. Interactive Segmentation Algorithms.- 1. Deillegalscription of the SIVOG System.- 2. Experimental Results.- 6. Temporal and Spatial Adaptive Processing.- 1. Introduction.- 2. Deillegalscription of the SIVOG System.- 3. Region and Temporal Adaptive Processing.- 4. Experimental Results.- 7. Summary and Future Work.- 1. Future Work.- References.- About the authors.
Inhaltsverzeichnis
List of Figures. List of Tables. Preface. Acknowledgments. 1. Introduction. 2. Review of Previous Work. 3. Automatic Segmentation. 4. Object Shape Postprocessing. 5. Interactive Segmentation Algorithms. 6. Temporal and Spatial Adaptive Processing. 7. Summary and Future Work. References. About the Authors. Index.
Klappentext
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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