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CVPR
2003
IEEE

Video Segmentation Based on Graphical Models

10 years 1 months ago
Video Segmentation Based on Graphical Models
This paper proposes a unified framework for spatiotemporal segmentation of video sequences. A Bayesian network is presented to model the interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notions of distance transformation and Markov random field are used to express spatio-temporal constraints. Given consecutive frames, an optimization method is proposed to maximize the conditional probability density of the three fields in an iterative way. Experimental results show that the approach is robust and generates spatio-temporally coherent segmentation results.
Kia-Fock Loe, Tele Tan, Yang Wang 0002
Added 12 Oct 2009
Updated 29 Oct 2009
Type Conference
Year 2003
Where CVPR
Authors Kia-Fock Loe, Tele Tan, Yang Wang 0002
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