首页> 外文会议>European Conference on Computer Vision(ECCV 2004) pt.4; 20040511-20040514; Prague; CZ >Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation
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Multiphase Dynamic Labeling for Variational Recognition-Driven Image Segmentation

机译:多相动态标记的变体识别驱动图像分割

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We propose a variational framework for the integration multiple competing shape priors into level set based segmentation schemes. By optimizing an appropriate cost functional with respect to both a level set function and a (vector-valued) labeling function, we jointly generate a segmentation (by the level set function) and a recognition-driven partition of the image domain (by the labeling function) which indicates where to enforce certain shape priors. Our framework fundamentally extends previous work on shape priors in level set segmentation by directly addressing the central question of where to apply which prior. It allows for the seamless integration of numerous shape priors such that - while segmenting both multiple known and unknown objects - the level set process may selectively use specific shape knowledge for simultaneously enhancing segmentation and recognizing shape.
机译:我们提出了一个变体框架,用于将多个竞争形状先验信息集成到基于水平集的分割方案中。通过针对级别集函数和(向量值)标记函数优化合适的成本函数,我们共同生成了一个分割(通过级别集函数)和图像域的识别驱动分区(通过标记)函数),以指示在何处执行某些形状先验。我们的框架通过直接解决在哪里应用哪个优先级的核心问题,从根本上扩展了水平集细分中关于形状优先级的先前工作。它允许无缝整合各种形状先验,以便-在分割多个已知和未知对象的同时-水平设置过程可以有选择地使用特定的形状知识,以同时增强分割和识别形状。

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