Intelligent video segmentation for extracting video objects
In order to meet the demand of modern multimedia technology, which shows an increasing interest in content-based manipulation of video information, Video object (VO) is introduced in MPEG-4 to address content-based functionalities. Therefore, an effective VO segmentation is a crucial processing step...
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sg-ntu-dr.10356-44532023-07-04T15:58:50Z Intelligent video segmentation for extracting video objects Mao, Jinghong. Ma, Kai-Kuang School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing In order to meet the demand of modern multimedia technology, which shows an increasing interest in content-based manipulation of video information, Video object (VO) is introduced in MPEG-4 to address content-based functionalities. Therefore, an effective VO segmentation is a crucial processing step in modern digital video processing. However, VO segmentation is intrinsically an ill-posed challenge and encounters three major concerns: computational complexity, in-accurate boundaries of segmented VOs, and integration of user's interaction. Although motion segmentation and spatio-temporal segmentation have their individual applications and advantages, the trend of the modern video process-ing methodology not only focus on the low-level features such as intensity/color, motion but also introduces the high-level semantic information to bridge the gap between the human visual system and computer processing. In this the-sis, we investigate three methodologies—motion segmentation, spatio-temporal segmentation, and semantic segmentation, for VO segmentation and contribute our new solutions to handle above-mentioned issues. Master of Engineering 2008-09-17T09:51:49Z 2008-09-17T09:51:49Z 1999 1999 Thesis http://hdl.handle.net/10356/4453 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Mao, Jinghong. Intelligent video segmentation for extracting video objects |
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In order to meet the demand of modern multimedia technology, which shows an increasing interest in content-based manipulation of video information, Video object (VO) is introduced in MPEG-4 to address content-based functionalities. Therefore, an effective VO segmentation is a crucial processing step in modern digital video processing. However, VO segmentation is intrinsically an ill-posed challenge and encounters three major concerns: computational complexity, in-accurate boundaries of segmented VOs, and integration of user's interaction. Although motion segmentation and spatio-temporal segmentation have their individual applications and advantages, the trend of the modern video process-ing methodology not only focus on the low-level features such as intensity/color, motion but also introduces the high-level semantic information to bridge the gap between the human visual system and computer processing. In this the-sis, we investigate three methodologies—motion segmentation, spatio-temporal segmentation, and semantic segmentation, for VO segmentation and contribute our new solutions to handle above-mentioned issues. |
author2 |
Ma, Kai-Kuang |
author_facet |
Ma, Kai-Kuang Mao, Jinghong. |
format |
Theses and Dissertations |
author |
Mao, Jinghong. |
author_sort |
Mao, Jinghong. |
title |
Intelligent video segmentation for extracting video objects |
title_short |
Intelligent video segmentation for extracting video objects |
title_full |
Intelligent video segmentation for extracting video objects |
title_fullStr |
Intelligent video segmentation for extracting video objects |
title_full_unstemmed |
Intelligent video segmentation for extracting video objects |
title_sort |
intelligent video segmentation for extracting video objects |
publishDate |
2008 |
url |
http://hdl.handle.net/10356/4453 |
_version_ |
1772826122194518016 |