Paper
19 August 1998 Fast and robust moving object segmentation technique for MPEG-4 object-based coding and functionality
Author Affiliations +
Abstract
Video object segmentation is an important component for object-based video coding schemes such as MPEG-4. A fast and robust video segmentation technique, which aims at efficient foreground and background separation via effective combination of motion and color information, is proposed in this work. First, a non-parametric gradient-based iterative color clustering algorithm, called the mean shift algorithm, is employed to provide robust dominant color regions according to color similarity. With the dominant color information from previous frames as the initial guess for the next frame, the amount of computational time can be reduced to 50%. Next, moving regions are identified by a motion detection method, which is developed based on the frame intensity difference to circumvent the motion estimation complexity for the whole frame. Only moving regions are further merged or split according to a region- based affine motion model. Furthermore, sizes, colors, and motion information of homogeneous regions are tracked to increase temporal and spatial consistency of extracted objects. The proposed system is evaluated for several typical MPEG-4 test sequences. It provides very consistent and accurate object boundaries throughout the entire test sequences.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ju Guo, JongWon Kim, and C.-C. Jay Kuo "Fast and robust moving object segmentation technique for MPEG-4 object-based coding and functionality", Proc. SPIE 3561, Electronic Imaging and Multimedia Systems II, (19 August 1998); https://doi.org/10.1117/12.319741
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Cited by 2 scholarly publications.
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KEYWORDS
Image segmentation

Video

Motion estimation

Affine motion model

Motion detection

Image processing algorithms and systems

Video coding

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