Segmenting multiple familiar objects under mutual occlusion

被引：9

作者：

Zhang, Qilong ^{[1
]}

Pless, Robert ^{[1
]}

机构：

[1] Washington Univ, Dept Comp Sci & Engn, 1 Brookings Drv, St Louis, MO 63130 USA

来源：

2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS | 2006年

关键词：

image segmentation; variational methods; shape priors; level set methods; mutual occlusion;

D O I：

10.1109/ICIP.2006.312454

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We address the problem of segmenting multiple similar objects by optimizing a Chan-Vese-like [1] functional with respect to a mixture of level set functions. We solve the variational formulation under this model allowing for similarity transforms. This allows shape priors to be enforced even in the presence of mutual occlusion, lifting the limitation in [2]. We show numerical results on example images to demonstrate the promise of our approach.

引用

页码：197 / +

页数：2

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