DREAM2S:: Deformable Regions driven by an Eulerian Accurate Minimization Method for image and video Segmentation

被引:104
作者
Jehan-Besson, S
Barlaud, M
Aubert, G
机构
[1] UNSA, CNRS, Lab I3S, F-06903 Sophia Antipolis, France
[2] UNSA, CNRS, Lab JA Dieudonne, F-06108 Nice 2, France
关键词
image segmentation; region segmentation; energy minimization; region-based active contours; region functionals; boundary functionals; shape optimization; shape gradient; partial differential equations; face segmentation; covariance matrix determinant; level sets;
D O I
10.1023/A:1023031708305
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper deals with image and video segmentation using active contours. We propose a general form for the energy functional related to region-based active contours. We compute the associated evolution equation using shape derivation tools and accounting for the evolving region-based terms. Then we apply this general framework to compute the evolution equation from functionals that include various statistical measures of homogeneity for the region to be segmented. Experimental results show that the determinant of the covariance matrix appears to be a very relevant tool for segmentation of homogeneous color regions. As an example, it has been successfully applied to face segmentation in real video sequences.
引用
收藏
页码:45 / 70
页数:26
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