Research on motion segmentation based on robust error model and Markov random field;

Video motion segmentation algorithm based on singular value decomposition;

A motion segmentation approach for content-based video representation in image sequence;

In the paper,moving object segmentation algorithm based on mean field theory (MFT) using maximum a posteriori estimation of Markov random field (MRF-MAP) is proposed.

In this paper, a moving object segmentation algorithm based on multiresolution MRF using 3D spatio-temporal wavelet transform is proposed.

Moving Object Segmentation is one of significant and challenging problems in computer vision.

Spatial-temporal moving object segmentation;

264 is replacing MPEG-2/4 in many multimedia applications,but moving object segmentation in the H.

Due to the development of streaming media and emerging of content-based functionalities in MPEG-4, moving object segmentation technology becomes a popular research in video field.

This paper proposes a novel moving object segmentation algorithm based on kernel density estimation and edge information to solve the color similarity problem between foreground and background.

Aimed at the moving objects segmentation problem with a moving background,a method of segmentation and tracking of moving objects was proposed.