Intelligent video segmentation for extracting video objects.
Date of Issue1999
School of Electrical and Electronic Engineering
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.
DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Nanyang Technological University